AU730522B1 - Continuous kernel image interpolation - Google Patents

Continuous kernel image interpolation Download PDF

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AU730522B1
AU730522B1 AU65251/99A AU6525199A AU730522B1 AU 730522 B1 AU730522 B1 AU 730522B1 AU 65251/99 A AU65251/99 A AU 65251/99A AU 6525199 A AU6525199 A AU 6525199A AU 730522 B1 AU730522 B1 AU 730522B1
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image
filter function
interpolation
function
coefficients
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Andrew Peter Bradley
Kai Huang
Dominic Yip
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Canon Inc
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4007—Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation

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Description

S&F Ref: 483312
AUSTRALIA
PATENTS ACT 1990 COMPLETE SPECIFICATION FOR A STANDARD PATENT
ORIGINAL
Name and Address of Applicant: Canon Kabushiki Kaisha 30-2, Shimomaruko 3-chome Ohta-ku Tokyo 146 Japan Actual Inventor(s): Dominic Yip Andrew Peter Bradley Kai Huang Address for Service: Invention Title: Spruson Ferguson St Martins Tower 31 Market Street Sydney NSW 2000 Continuous Kernel Image Interpolation ASSOCIATED PROVISIONAL APPLICATION DETAILS [33] Country [31] Applic. No(s) Australia PP7799 [32] Application Date 18 December 1998 The following statement is a full description of this invention, including the best method of performing it known to me/us:- 5815c CONTINUOUS KERNEL IMAGE INTERPOLATION Field of Invention The present invention relates to the field of resolution conversions of digital data and in particular digital image data. The current invention is particularly advantageous for a resolution conversion implementation that uses samples from a continuous kernel as coefficients in the convolution operation. The current invention also provides an efficient software algorithm to implement resolution conversion.
Background of Invention A filter function used in digital data resolution conversion is often called a convolution kernel, a filter kernel or just a kernel. When a kernel produces data that passes through original data points of a sampled signal, it is often called an interpolating kernel and when the interpolated data produced is not constrained to pass through the original data points it is often called an approximating kernel.
Prior art kernels for digital data resolution conversion include the nearest neighbour linear, quadratic and cubic kernels. The NN kernel is the simplest method of interpolation,, simply interpolating the image with the pixel value that is spatially nearest to the required pixel value. This method works quite well when the scaling ratio is an integer multiple of the original data as it introduces no new values, ie.
no new colours, and preserves sharp edges. However, at other ratios the NN kernel has the disadvantage of shifting edge locations which often produces visible distortions in the output image, especially in images containing text or fine line details. Linear interpolation on the other hand allows for the introduction of new grey levels (or colours) that are effectively used to position edges at sub-pixel locations. This has the advantage of reducing the effect of shifted edge locations, however sharp edges can now appear to be blurred. Quadratic and cubic interpolation provide steeper step responses and therefore less edge blurring, however, the steeper response results in an overshoot on either side of the edge. These overshoots can make the edges in natural images appear sharper, but on text, fine lines, or on other computer generated graphics these overshoots are clearly visible and detract from the perceived image quality and text legibility.
r.F=Prr??A1 I rnrA (4R'All 9 [o:\cisra\rc\rc03l48331t2AU.doc:SaF CFPi~99AI I PflA~ (4R3~1~~ Io:\cisra\rc\rc03148331 2AU.doc:SaF Hardware to perform two dimensional image interpolation using a method of cubic convolution is known whereby pre-calculated values of the two-dimensional cubic convolution kernel are stored in a look-up table (LUT) and then simultaneously 16 (4x4) coefficient values are read and multiplied with 16 pixels in the original image surrounding the pixel location to be interpolated. Storing the coefficient values in a look-up table removes the need to calculate the coefficients at each interpolated pixel and therefore increases the speed of execution of the algorithm.
Another technique performs two-dimensional interpolation by first interpolating the rows of an image and then interpolating the columns of the image. Up to 4 coefficients for each of the one-dimensional convolution kernels are again read from a LUT, multiplied with data, and summed to produce an interpolated pixel. However, this implementation, which is commonly referred to as a "separable implementation", is not as fast as the two-dimensional implementation discussed above, although significant reductions in the memory requirements of the LUT may be obtained.
There is a problem however, with both of these known methods in that precalculating values and storing them in a LUT introduces an error between the actual coefficient value required for the interpolation and the closest value stored in the LUT.
Storing more values in the LUT can reduce this error, however, this can drastically increase the amount of storage required for the LUT.
It is an object of the present invention to ameliorate one or more disadvantages of the prior art.
Summary of the Invention One or more exemplary aspects of the invention are listed below, but are not limited thereto.
According to one aspect of the invention there is provided a method of converting a first set of discrete data values to a second set of discrete data values, the method comprising the following steps: calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values; CFP I 103A RC03 (483312) [o:\cisra\rc\rr031AUspeci .doc: SaF cFP11o3Au RCO3 (483312) [o:\cisra\rc\rc~3JAUspeci.dac:SaF -3- (ii) calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter functions; (iii) storing said filter function coefficients; (iv) accessing said stored filter function coefficients; and performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values.
According to another aspect of the invention there is provided an apparatus for converting a first set of discrete data values to a second set of discrete data values, the apparatus comprising: calculator means for calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter functions; storage means for storing said filter function coefficients; storage access means for accessing said stored filter function coefficients; and interpolation means for performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values.
According to still another aspect of the invention there is provided a computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of converting a first set of discrete data values to a second set of discrete data values, said program comprising: code for calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values; code for calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter function; code for storing said filter function coefficients; code for accessing said stored filter function coefficients; and CFP1103AU RC03 (483312) [o:%disra\rc\rc03jAUspeci.doc:SaF cFP11o3Au RCO3 (483312) (o:\cisra\rc'rcO3IAUspecidoc:SaF -4code for performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values.
According to still another aspect of the invention there is provided a method of performing interpolation on a pixel-based image, the method comprising the steps of: calculating a scaling factor of a first image compared to a second image; (ii) calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; (iii) storing said filter function coefficients; (iv) detecting incoming pixels of said first image; accessing said stored filter function coefficients; and (vi) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided an apparatus for performing interpolation on a pixel-based image, the apparatus comprising: calculator means for calculating a scaling factor of a first image compared to a second image, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; storage means for storing said filter function coefficients; detection means for detecting incoming pixels of said first image; coefficient access means for accessing said stored filter function coefficients; and interpolator for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided a computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing interpolation on a pixel-based image, said program comprising: CO4 4-Al I De-Aj IAQIII I-\r.icr\rc\rr031AUsDec.doc:SaF code for calculating a scaling factor of a first image compared to a second image, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; code for storing said filter function coefficients; code for detecting incoming pixels of said first image; accessing said stored filter function coefficients; and code for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided a method of performing interpolation on a pixel-based image, the method comprising the steps of: inputting dimension values of a first image and a second image: (ii) calculating a scaling factor of said first image compared to said second image; (iii) computing interpolation indicators for said second image based on said scaling factor; (iv) calculating filter function coefficients, according to said interpolation indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; storing said filter function coefficients; (vi) detecting incoming pixels of said first image; and (vii) accessing said stored filter function coefficients; and (viii) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided an apparatus for performing interpolation on a pixel-based image, said apparatus comprising: input means for inputting dimension values of a first image and a second image: calculator means for calculating a scaling factor of said first image compared to said second image, computing interpolation indicators for said second image based on said scaling factor, and calculating filter function coefficients, according to said interpolation CFP1 103AU RC03 (483312) (o:%disra~rc~c03 AUspec.doc:SaF cFP1 1O3AU RCO3 (483312) (o:\cisra\rc\rco3jAUspecidac:SaF indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; storage means for storing said filter function coefficients; detection means for detecting incoming pixels of said first image; and coefficient access means for accessing said stored filter function coefficients; and interpolator for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided a computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing interpolation on a pixel-based image, said program comprising: code for inputting dimension values of a first image and a second image: code for calculating a scaling factor of said first image compared to said second image; code for computing interpolation indicators for said second image based on said scaling factor; code for calculating filter function coefficients, according to said interpolation indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; code for storing said filter function coefficients; code for detecting incoming pixels of said first image; and code for accessing said stored filter function coefficients; and code for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
According to still another aspect of the invention there is provided a method of performing image interpolation, the method comprising the steps: inputting dimension values of a first image and a second image; CFP110AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF (ii) calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values; (iii) computing pairs of interpolation indicators according to said first and second sampling limit values; (iv) calculating fractional first and second coordinate values using said interpolation indicators; calculating filter function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; (vi) storing said filter function coefficient values in a table; (vii) detecting input pixel values of said first image; (viii) accessing said stored filter function coefficients; and (ix) performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
According to still another aspect of the invention there is provided an apparatus for performing image interpolation, the apparatus comprising: input means for inputting dimension values of a first image and a second image; calculator means for calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values, computing pairs of interpolation indicators according to said first and second sampling limit values, calculating fractional first and second coordinate values using said interpolation indicators, and calculating filter function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; storage means for storing said filter function coefficient values in a table; detection means for detecting input pixel values of said first image; coefficient access means for accessing said stored filter function coefficients; and interpolator for performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
.FP113AU RC03 (483312) [o:\cisra\rc\rc3]AUspeci.doc:SaF According to still another aspect of the invention there is provided a computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing image interpolation, said program comprising: code for inputting dimension values of a first image and a second image; code for calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values; code for computing pairs of interpolation indicators according to said first and second sampling limit values; code for calculating fractional first and second coordinate values using said interpolation indicators; code for calculating filter 'function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; code for storing said filter function coefficient values in a table; detecting input pixel values of said first image; code for accessing said stored filter function coefficients; and code for performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
According to still another aspect of the invention there is provided a method of performing interpolation on a first pixel-based image, the method comprising the steps of: determining dimension values for a second image; (ii) calculating a plurality of filter function coefficients based on said dimension values; (iii) storing said filter function coefficients; (iv) detecting incoming pixels of said first image; accessing said stored filter function coefficients; and (vi) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
CFP1O3AU RC03 (483312) [o:\cisra\rc\rcO31AUspeci.doc:SaF Fig. 2 is a flow diagram showing the preferred method of control provided by the logic and control unit of Fig. 1; Fig. 3 is a flow diagram showing the preferred setup procedure performed provided by the logic and control unit of Fig. 1; Fig. 4 is a schematic block diagram showing the index generator of Fig. 1 in more detail; Fig. 5 is a schematic block diagram showing the coefficient calculator of Fig. 1 in more detail; Fig. 6 shows the preferred address format of a coefficient look-up table in accordance with the preferred embodiment; Fig. 7 is a schematic block diagram showing a system for providing kernel coefficients in accordance with a second embodiment of the present invention; Fig. 8 is a flow diagram showing the preferred method of control provided by the logic and control unit of Fig. 7; Fig. 9 is a schematic block diagram showing a system for providing kernel coefficients in accordance with a second embodiment of the present invention; Fig. 10 is a flow diagram showing the preferred method of control provided by the logic and control unit of Fig. 9; and Fig. 11 is a diagram showing a general purpose computer upon which the embodiments of the present invention can be implemented.
Detailed Description Where reference is made in any one or more of the drawings to steps and/or features, which have the same reference numerals, those steps and/or features are for the purposes of the description have the same functions and or operations, unless the contrary appears.
The preferred embodiment overcomes the problem of having to store multiple precalculated convolution values by populating the LUT, before interpolation begins, with only those coefficients required for the particular re-sampling ratio. In this way, there is no error introduced in the coefficient values and the storage required is reduced by CFP I 103A RC03 (483312) [o:\cisra\rc\rc03)AUspeci.doc:SaF CFP1 1O3AU RCO3 (483312) (o:\cisra\rc\rcO3]AUspeci.doc:SOF -11 recognising the fact that only a limited number of coefficient values are required for any one resolution conversion ratio.
For scaling factors that can be expressed as integer or rational fractions, eg. 2, 5/8, 8/5, 10/1, the number of coefficients required is limited and these values are repeatedly used along the horizontal and vertical scan lines. The preferred embodiment is a method and apparatus for populating the LUT, before interpolation begins, with only those coefficients required for the particular re-sampling ratio. In this way, both the storage required for the LUT and the error in the stored coefficients are minimised. A second embodiment of the present invention has a further advantage of allowing the LUT to hold a two-dimensional kernel with minimal storage. Using a two-dimensional kernel not only has a speed advantage over the separable implementation, but also allows kernels to be used that cannot be implemented using separable techniques.
Examples of integer or rational scaling factors are the scaling factor between display standards such as VGA (640x480) and (1024x768) XGA which is 5/8; and VGA and SVGA (800x600) which is 5/4.
Fig. 1 shows a system 101 that uses the preferred embodiment to provide kernel coefficients to other interpolation circuits to perform interpolation. The system 101 contains a logic and control unit 103 connected to an index generator 105 and a fraction generator 107. The output of the fraction generator is connected to a coefficient calculator 113 which supplies kernel coefficients to two kernel coefficient look-up tables 109,111. The outputs of the two kernel coefficient look-up tables 109,111 are connected to a kernel coefficient readout circuit 115. The logic and control unit 103 is also connected to an index generator 105 which in turn supplies pairs of indices j), according to constraints maxx, maxy and the width of the output image, to both the fraction generator 107 and the kernel coefficient readout circuit 115.
The system 101 has two phases of operation: initialisation and execution. During the initialisation phase the logic and control unit 103 receives the input image width and height (number of pixels), and output image width and height (number of pixels), and calculates the horizontal sampling increment stepx, and vertical sampling increment stepy CFP1103AU RC03 (483312) jo:\dsra\rcVW3]3AUspecj.doc:SaF CFP11O3AU RCO3 (483312~ fo:\cisra\rc\rcO3lAUspea doc:SaF -12which are provided to the fraction generator 107, and the horizontal maximum cycle count max x and vertical maximum cycle count maxy which are provided to the index generator 105. The index generator 105 computes sequences of pairs of indices j) according to constraints max x and maxy. The indices are provided to the fraction generator 107. Each pair of indices is then used by the fraction generator 107 to calculate fracx andfracy, which are the fractional parts of the next x and y coordinates respectively.
The fractionsfrac x andfracy are calculated using the following equations: fracx =fraction_of(i*stepx) fracy =fraction_of(j*stepy,) One of these fractions is then used by the coefficient calculator 113 to calculate the kernel coefficients for the horizontal kernel or the vertical kernel. One or more coefficients can be calculated at any time. These coefficients are then written into one of the kernel coefficient look-up tables 109,111. This process is repeated until all max x horizontal and maxy vertical kernel coefficients are calculated.
During the execution phase, the logic and control unit 103 instructs the index generator 105 to compute sequences of pairs of indices j) according to constraints maxx, maxy and the width of the output image. Each index pair is then used by the coefficient readout circuit 15. to read out one or more coefficients from the kernel coefficient look-up tables 109,111. The coefficient readout circuit 115 may output all coefficients that it receives, or it can select only a number of its coefficients to output.
Fig. 2 is a flow diagram showing the preferred method of control provided by the logic and control unit 3 for the first embodiment. The method commences at step 201 where any necessary processes and parameters are initialised, such as process counters.
At the next step 203, the logic control unit 103 performs a setup calculating the sampling increments stepx and stepy, and the maximum cycle count max x and maxy. The process continues at step 205, where the logic and control unit 3 starts the index generator 105 to generate all coefficients in the horizontal kernel. The index generator 105 generates index i from 0 to max x and the fraction generator 107 generates all the fractions accordingly.
All coefficients are written into the kernel coefficient look-up table 111. In the next step CFP110AU RC03 (483312) lo:\cisra\rc\rc03]AUspeci.doc:SaF CFP1 1O3AU RCO3 (483312) [oAcisra\rc\rcO3]AUspeci.doc~SaF -13- 207, all the modules perform the same procedure to generate all coefficients in the vertical kernel, and all coefficients are written into kernel coefficient look-up table 109. The process continues at the next step 208, where the logic and control unit 103 checks whether there are any incoming pixels. If there are, the LCU 103 signals the index generator 105 to generate indices for the coefficient readout circuit. In the next step 210, the coefficient readout circuit then reads out appropriate coefficients from the look-up tables so that interpolation on that source pixel can be performed.
Fig. 3 is a flow diagram showing the preferred setup procedure preformed by the logic and control unit 103. The procedure commences at step 302, where the LCU first calculates the horizontal sampling increment stepx by dividing the input image width with output image width. Similarly, the logic and control unit 103 calculates the vertical sampling increment stepy by dividing input image height with output image height. In the next step 305, the LCU 103 calculates the highest common factor (HCF) between the input image width and output image width. The highest common factor (HCF) between the input image height and the output image height is also calculated. The HCF is preferably calculated using the Euclidean algorithm (ie: Euclid's algorithm) which is known in the prior art. The procedure continues at the next step 307, where the output image width is divided by the HCF and the LCU 3 determines if the dividend is less than the maximum table size. If the dividend is less than the maximum table size, then the dividend is the maximum horizontal cycle count max x at step 309. If it is greater, then the LCU 103 goes through all the integers from 2 to maximum table size, at step 311, and determines which integer m makes the product stepx m closest to an integer. The maximum horizontal cycle count max x is then equal to m, at step 313. The procedure then continues at steps 315, 317, 319 and 321, where the LCU uses the same method to determine maxy.
Fig. 4 shows the index generator 105 in more detail. On command from the logic and control unit 103, the index generator 105 operates in one of the two modes: initialisation and execution. In the initialisation mode, the index generator first resets both an x-counter 401 and a y-counter 403 to 0. Thereafter, whilst being clocked the x- CFP1103AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF CFP1IO3AU RCO3 (483312) IaAcisra\rc\rcO3IAUspecj.dacSaF 14counter 401 is incremented until it reaches maxx-1, it is reset to 0, and y-counter 403 is clocked to incremented until it reaches maxy-1. The initialisation phase finishes at this point.
When the index generator 105 is in execution mode, the x-counter 401 and y-counter 403 are firstly reset to 0, and a register 405 is loaded with (image width As enabled by the logic and control unit 103, the x-counter 401 is incremented until it reaches maxx-1, and the register 405 is decremented by the decrementor 407. As the x-counter 401 reaches maxx-1, it is reset to 0. As the register 405 reaches 0, the y-counter is incremented, and x-counter 401 is reset to 0. This procedure is repeated until the y-counter 403 reaches maxx-1. At this point a frame of interpolated output image is produced, and the index generator 105 becomes idle.
The coefficient calculator 113 will now be described in more detail with reference to Fig. 5. According to the configuration signal from the logic and control unit 103 on line 521, one of the fractions from x and y coordinates stored in latch 517 is added by an adder 519 to an offset generated by an offset generator 501 according to information from LCU 103 on line 523. In the preferred embodiment, the offset can be 0, 1 or 2. The sum is then input to a pipeline of delays (525,527,529) multipliers (505,507,509) and adders (511,513,515) and multiplied and added with coefficients A, B, C'and D generated by the kernel coefficient selector 505. The coefficients generated depend on the kernel that is used for interpolation (eg. cubic, quadratic, sinc, etc), and the configuration information from LCU 103, which indicates what offset is added to the fraction. For example, when a cubic kernel with parameter a=0.5 is used, A equals to 2, B equals C equals to 0, and D equals to 1. The outputs of each adder (511,513,515) are temporarily stored in registers (531,533,535) before being forwarded to the next multiplier stage.
Fig. 6a illustrates the preferred address format of the kernel coefficient look-up table 111. The "offset" field can range from 0 to 3, where 0 represents an offset of 1 represents ar offset of 0, 2 represents an offset of 1, and 3 represents an offset of 2. The x index is obtained from the index generator 105. Fig. 6b illustrates the preferred address format to the kernel coefficient look-up table 109. The "offset" field can range from 0 to CFP1103AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF CFP11O3AU RCO3 (483312) [o:\cisra\rc\rcO3jAUspeci.doc:SaF 3, where 0 represent an offset of-1, 1 represents an offset of 0, 2 represent an offset of 1, and 3 represent an offset of 2. The y index is obtained from the index generator 105.
For a more detailed explanation of the first embodiment reference is made to the following example.
Example 1 In this example the system 1 of the first embodiment is scaling an image with VGA resolution (640x480) to XGA resolution (1024x768).
During the setup phase of the logic and control unit 103 it calculates that: stepx and stepy are both 5/8; (ii) the HCF for input image width and output image width is 128; (iii) the HCF for input image height and output image height is 96; and (iv) max x and maxy are both 8, which are both smaller than the maximum table size.
Next, the LCU 103 signals the index generator 105 to begin generating sequences of indices according to max x and maxy, and the sequence that it will generate is From the above sequence of indices, the fraction generator 107 will generate the following sequence of pairs of fractions: From this sequence, the coefficient calculator 113 evaluates the kernel equation using those fractions, and writes 8 entries into kernel coefficient LUT 111, representing the horizontal kernel, and 8 entries into kernel coefficient LUT 109, representing the vertical kernel. Each of these entries has 4 values, one for each offset. (For cubic interpolation, the offset can be 0, 1, or 2).
After the LUTs (109,111) are initialised, the system is now ready to accept pixels.
When enough pixels have come to generate the first interpolated pixel, the logic and CFP1 103AU RC03 (483312) [o:\disra\rc\rc03]AUspeci .doc: SaF cF1I3 UR O 431)[:csarmc3A seia:a -16control unit 103 will signal the index generator 105 to start generating pairs of indices.
The following sequence will be generated: (this cycle will continue until 1024 pairs of indices are generated.) This sequence is used to access the LUTs 109 and 111 and the stored coefficients are then used to interpolate the required sample.
Referring to Fig. 7, there is shown in block diagram form a second embodiment which is directed to allow the LUT 701 to work with kernels which are not separable.
When the interpolation kernel cannot be separated into a ID horizontal kernel and a ID vertical kernel, the coefficient calculator 703 requires both fracx and fracy to calculate the kernel coefficients. In the initialisation phase, instead of incrementing only one of the indices and leaving the other to 0, the index generator 705 generates a sequence of maxx*maxy pairs of indices (ij) to the fraction generator 707. The fraction generator 707 generatesfrac x andfracy according to the pair of indices it receives, and for each pair of fractions the coefficient calculator 703 computes k*l kernel coefficients for it, where k is the number of rows in the kernel matrix and I is the number of columns in the kernel matrix. In the preferred embodiment both k and I are equal to 4.
Fig. 8 is a flow diagram showing the preferred method of control provided by the logic and control unit 709 in the second embodiment. The method commences at step 803 where the system 700 performs a setup procedure as described in Fig. 3. The process continues at step 805, where the LCU 709 signals the index generator 705 to begin generating sequences of indices in the following fashion: reset both i andj to 0; (ii) in every cycle, increment i until i reaches max x 1; (iii) incrementj, and reset i to 0; (iv) repeat steps (ii) and (iii) untilj reaches maxy-1 and i reaches max x 1.
After that the kernel coefficient look-up table 701 should be filled up, and the initialisation phase is finished. At step 807, when enough incoming pixels have arrived CFP1103AU RC03 (483312) [o:\cisra\rc\rc03]Auspec.doc:SaF -17for the interpolation system 700 to perform interpolation, the LCU 709 will signal the index generator 705 to generate pairs of indices in the same fashion as described above.
Further, when enough incoming pixels have arrived for the interpolation system 700 to perform interpolation the coefficient readout circuit 711 will read the appropriate entries in the kernel coefficient look-up table 701, at step 809, to provide the k*l kernel coefficients for interpolation, where k is the number of rows in the kernel matrix and I is the number of columns in the kernel matrix.
For a more detailed explanation of the second embodiment reference is made to the following example.
Example 2 In this example the system 700 of the second embodiment is scaling an image with VGA resolution (640x480) to XGA resolution (1024x768).
During the setup phase of the logic and control unit 709 it calculates that stepx and stepy are both 5/8, and max x and maxy are both 8. After that, the LCU 709 signals the index generator 705 to begin generating sequences of indices according to max x and maxy, and the sequence that it will generate is From the above sequence of indices, the fraction generator 707 will generate the following sequence of pairs of fractions: From this sequence, the coefficient calculator 703 evaluates the 701 kernel equation using those fractions, and writes 64 entries into kernel coefficient LUT 701. Each of these entries has 16 values, one for each combination of offsets to x and y fractions. (For cubic interpolation, the offset combinations can be After the LUT 701 is initialised, the system 700 is now ready to accept pixels.
When enough pixels have come to generate the first interpolated pixel, the logic and CFP1103AU RC03 (483312) lo:\rjsra\rc~rc03]Aspeci.doc:SaF cFP1 1O3AU RCO3 (483312) [a\cisra\rcVcO3jAUspeci.doc:SaF -18control unit 709 will signal the index generator to start generating pairs of indices. The following sequence will be generated: (this cycle will continue until 1024 pairs of indices are generated) This sequence is used to access the LUTs 109 and 111 and the stored coefficients are then used to interpolate the required sample.
A third embodiment will now be described with reference to Fig. 9 and Fig. The third embodiment is directed to alleviate the need to calculate the HCF between the output image width and input image width, and the HCF between the output image height and input image height. This embodiment contains the same module as the first embodiment, however, the need for the LCU 901 to use HCFs to calculate max x and maxy is removed. The lines 117, 119 carrying the signals max x and maxy of the first embodiment are removed. Further, a line 913 carrying the signal zerofrac is fed from the fraction generator 903 to the LCU 901. The LCU 901 determines the values of max, and maxy by observing the status of the signal zerofrac from the fraction generator 903, which is asserted when the fractional part of x or y is close to or equal to 0. When zerofrac is asserted, the LCU 901 records what value of the index i orj corresponds to that assertion, and that would be max x and maxy respectively. In the third embodiment, in the initialisation phase the index generator 905 firstly resets j to 0, and increments the index i until either the signal zerofrac is asserted, or the maximum table size is reached.
After that, it resets i to 0 and increments the indexj from 0 until either the signal zerofrac is asserted, or the maximum table size is reached. In the execution phase, the index generator 905 generates pairs of indices (ij) according to the max x and maxy found in exactly the same way as it does in first embodiment.
The overall operation of the LCU 901 in the initialisation phase is further explained with reference to Fig. 10. At step 1001, the LCU 901 calculates the horizontal sampling increment stePx and vertical sampling increment stepy. Next at step 1003, the LCU 901 signals the index generator 905 to start incrementing index i, and observe the index i and ('FP113AU RC03 (4833121 lo:\cisra~rc\rc03]A~specd.doc:SaF CF1OA C3(832 o'csarIc~Ase~a:a -19the signal zerofrac. When zerofrac is 1 at step 1005, it assigns i to max x at step 1007.
When zerofrac is 0 and i equals to the maximum table size, the LCU 901 determines the value of max x by finding an integer m such that stepx*m is closest to an integer at step 1011. The process continues at step 1013, where m is assigned to be max x At step 1015, the LCU 901 signals the index generator to start incrementingj, and reset i to 0. The LCU 901 then observes the indexj and the signal zerofrac at step 1017. When zerofrac is 1, it assignsj to maxy at step 1019. When zerofrac is 0 andj reaches the maximum table size at step 1021, the LCU 901 determines the values of maxy by finding an integer n such that stepy*n is closest to an integer at step 1023. Finally at step 1025, n is assigned to be maxy.
For a more detailed explanation of the third embodiment reference is made to the following example.
Example 3 In this example the system 900 of the third embodiment is scaling an image with VGA resolution (640x480) to XGA resolution (1024x768).
During the setup phase of the logic and control unit 901 it calculates that stePx and stepy are both 5/8. After that, the LCU 901 signals the index generator 905 to begin generating sequences of indices with only i incrementing. The sequence that it will generate is When i reaches 8, the x fraction will be 0 and the signal zerofrac will be asserted. At that point, LCU 901 assigns 7 to max x Next, the LCU 901 signals the index generator 905 to begin generating sequences of indices with onlyj incrementing. The sequence that it will generate is Whenj reaches 8, the y fraction will be 0 and the signal zerofrac will be asserted. At that point, LCU 901 assigns 7 to maxy.
From the above sequences of indices, the fraction generator 903 will generate the following sequence of pairs of fractions: CFP1 10AU RC03 (483312) [o:\cisra\\rcrc03)AUspeci.doc:SaF From this sequence, the coefficient calculator 907 evaluates the kernel equation using those fractions, and writes 8 entries into kernel coefficient LUT 909, representing the horizontal kernel, and 8 entries into, kernel coefficient LUT 911, representing the vertical kernel. In the preferred embodiment, each of these entries has 4 values, one for each offset. (For cubic interpolation, the offset can be 0, 1, or 2).
After the LUTs 909,911 are initialised, the system 900 is now ready to accept pixels. When enough pixels have come to generate the first interpolated pixel, the logic and control unit 901 will signal the index generator 905 to start generating pairs of indices. The following sequence will be generated: (this cycle will continue until 1024 pairs of indices are generated) This sequence is used to access the LUTs 109 and 111 and the stored coefficients are then used to interpolate the required sample.
Preferred Embodiment of Apparatus(s) The embodiments are preferably implemented as part of a conventional generalpurpose computer system, such as the computer system 1100 shown in Fig. 11, wherein the systems 101, 700 and 900 of Figs. 1, 7 and 9, respectively can be implemented as part of a plug-in board. Alternatively, the systems 101, 700 and 900 can be implemented as part of a video interface (not shown) or graphics processor(not shown).
The processes described with reference to Figs. 1 to 10 can also be implemented as software executing on the computer system 1100. In particular, the steps of the methods are effected by instructions in the software that are carried out by the computer. The software can be divided into two separate parts; one part for carrying out the methods of the embodiments; and another part to manage the user interface between the latter and the user. The software can be stored in a computer readable medium, including the storage devices described below, for example. The software is loaded into the computer from the computer readable medium, and then executed by the computer. A computer readable medium having such software or computer program recorded on it is a computer program CFP1103AURC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF -21 product. The use of the computer program product in the computer preferably effects an advantageous apparatus for orientating a character stroke or n-dimensional finite space curves in accordance with the embodiments of the invention.
The computer system 1100 has a computer module 1102, a video display 1116, and input devices 1118, 1120. In addition, the computer system 1100 can have any of a number of other output devices including line printers, laser printers, plotters, and other reproduction devices connected to the computer module 1102. The computer system 1100 can be connected to one or more other computers via a communication interface 1108c using an appropriate communication channel 1130 such as a modem communications path, a computer network, or the like. The computer network can include a local area network (LAN), a wide area network (WAN), an Intranet, and/or the Internet The computer module 1102 has a central processing unit(s) (simply referred to as a processor hereinafter) 1104, a memory 1106 which can include random access memory (RAM) and read-only memory (ROM), input/output (IO) interfaces 1108, a video interface 1110, and one or more storage devices generally represented by a block 1112 in Fig. 1. The storage device(s) 1112 can include one or more of the following: a floppy disc, a hard disc drive, a magneto-optical disc drive, CD-ROM, magnetic tape or any other of a number of non-volatile storage devices well known to those skilled in the art.
Each of the components 1104 to 1112 and the system 101 are typically connected to one or more of the other devices via a bus 1114 that in turn has data, address, and control buses.
The video interface 1110 is connected to the video display 1116 and provides video signals from the computer 1102 for display on the video display 1116. User input to operate the computer 1102 can be provided by one or more input devices 1308. For example, an operator can use the keyboard 1118 and/or a pointing device such as the mouse 1120 to provide input to the computer 1102.
The computer system 1100 is simply provided for illustrative purposes and other configurations can be employed without departing from the scope and spirit of the CFP1103AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF -22invention. Exemplary computers on which the embodiment can be practiced include the IBM-PC or compatibles, one of the Macintosh TM family of PCs, Sun Sparcstation TM, arrangements evolved therefrom or the like. The foregoing are merely exemplary of the types of computers with which the embodiments of the invention can be practiced.
Typically, the processes of the embodiments, described hereinafter, are resident as software or a program recorded on a hard disk drive (generally depicted as block 1112 in Fig. 11) as the computer readable medium, and read and controlled using the processor 1304. Intermediate storage of the program and pixel data and any data fetched from the network can be accomplished using the semiconductor memory 1106, possibly in concert with the hard disk drive 1112.
In some instances, the program can be supplied to the user encoded on a CD-ROM or a floppy disk (both generally depicted by block 1112), or alternatively could be read by the user from the network via a modem device connected to the computer, for example.
Still further, the software can also be loaded into the computer system 1300 from other computer readable medium including magnetic tape, a ROM or integrated circuit, a magneto-optical disk, a radio or infra-red transmission channel between the computer and another device, a computer readable card such as a PCMCIA card, and the Internet and Intranets including email transmissions and information recorded on websites and the like. The foregoing are merely exemplary of relevant computer readable mediums. Other computer readable mediums can be practiced without departing from the scope and spirit of the invention.
The foregoing only describes one embodiment of the present invention, however, modifications and/or changes can be made thereto by a person skilled in the art without departing from the scope and spirit of the invention.
In the context of this specification, the word "comprising" means "including principally but not necessarily solely" or "having" or "including" and not "consisting only of'. Variations of the word comprising, such as "comprise" and "comprises" have corresponding meanings.
CFP1103AU RC03 (483312) [o:\cisra\rc~rc03]AUspeci.doc:SaF cF1oA C3 (831)[:csarlcOj~pc~o:a

Claims (70)

  1. 23- The claims defining the invention are as follows: 1. A method of converting a first set of discrete data values to a second set of discrete data values, the method comprising the following steps: calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values; (ii) calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter functions; (iii) storing said filter function coefficients; (iv) accessing said stored filter function coefficients; and performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values. 2. A method according to claim 1, wherein step (ii) includes the sub-steps of: computing interpolation indicators for said second image based on said scaling factor; and calculating said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators. 3. A method according to claim I, wherein the filter function is a cubic function. 4. A method according to claim 1, wherein the filter function is a linear function. 5. The method according to claim 1, wherein the filter function is a quadratic function. 6. The method according to claim I, wherein the filter function is a weighted sinc function. CFP110AU RC03 (483312) lo:\cisra\rc\rc03]Auspeci .doc: SaF cF1OA C3(831)LImr~~cOI~pc~a:a -24- 7. The method according to claim 1, wherein said first image is a colour image. 8. The method according to claim 1, said method comprising the further step of convolving each pixel of said first image with said filter function. 9. The method according to claim 1, wherein said filter function is a one-dimensional function. 10. The method according to claim 1, wherein said filter function is a two-dimensional function. 11. The method according to claim 1, wherein a plurality of filter function coefficients are calculated simultaneously. 12. An apparatus for converting a first set of discrete data values to a second set of discrete data values, the apparatus comprising: calculator means for calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter functions; storage means for storing said filter function coefficients; storage access means for accessing said stored filter function coefficients; and interpolation means for performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values. 13. The apparatus according to claim 12, wherein said calculator means computes interpolation indicators for said second image based on said scaling factor, and calculates CFP110AU RC03 (483312) [o:%disra\rc-c03AUspeci.doc:SaF CFPI1O3AU RCO3 (483312) [o:\cisra\rc~rcO3]AUspeci.dac:SaF said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators. 14. The apparatus according to claim 12, wherein the filter function is a cubic function. The apparatus according to claim 12, wherein the filter function is a linear function. 16. The apparatus according to claim 12, wherein the filter function is a quadratic function. 17. The apparatus according to claim 12, wherein the filter function is a weighted sinc function. 18. The apparatus according to any one of claims 12 to 15, wherein said first image is a colour image. 19. The apparatus according to claim 12, said apparatus further comprising convolving means for convolving each pixel of said first image with said filter function. The apparatus according to claim 12, wherein said filter function is a one- dimensional function. 21. The apparatus according to claim 12, wherein said filter function is a two- dimensional function. 22. The apparatus according to claim 12, wherein a plurality of filter function coefficients are calculated simultaneously. CFP1522AU RC03 (483312) fo:\clsra\rc\rcO31483312AU.doc:edo cFP1522Au RCO3 (483312) (o:\cIsra'rc~rcO3148331 2AU.doc:eda -26- 23. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of converting a first set of discrete data values to a second set of discrete data values, said program comprising: code for calculating a scaling factor of said first set of discrete data values compared to said second set of discrete data values; code for calculating a plurality of filter function coefficients, based on said scaling factor, utilising at least one of a plurality of filter function; code for storing said filter function coefficients; code for accessing said stored filter function coefficients; and code for performing interpolation on said first set of discrete data values, using said accessed filter function coefficients, to generate said second set of discrete data values.
  2. 24. The computer readable medium according to claim 23, said program further comprising: code for computing interpolation indicators for said second image based on said scaling factor; and code for calculating said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators. The computer readable medium according to claim 23, wherein the filter function is a cubic function.
  3. 26. The computer readable medium according to claim 23, wherein the filter function is a linear function. CFP1 103AU RC03 (483312) [o:\cisra\rc\rc03lAUspeci.doc:SaF CFP1 1O3AU RCO3 (483312) [oAcisra\rc\rcO3~AUspectdoc:SaF -27-
  4. 27. The computer readable medium according to claim 23, wherein the filter function is a quadratic function.
  5. 28. The computer readable medium according to claim 23, wherein the filter function is a weighted sinc function.
  6. 29. The computer readable medium according to claim 23, wherein said first image is a colour image.
  7. 30. The computer readable medium according to claim 23, said program further comprising code for convolving each pixel of said first image with said filter function.
  8. 31. The computer readable medium according to claim 23, wherein said filter function is a one-dimensional function.
  9. 32. The computer readable medium according to claim 23, wherein said filter function is a two-dimensional function.
  10. 33. The computer readable medium according to claim 23, wherein a plurality of filter function coefficients are calculated simultaneously.
  11. 34. A method of performing interpolation on a pixel-based image, the method comprising the steps of: calculating a scaling factor of a first image compared to a second image; (ii) calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; (iii) storing said filter function coefficients; (iv) detecting incoming pixels of said first image; accessing said stored filter function coefficients; and CFP1522AU RC03 (483312) Fo:\cisra\rc\rc03l48331 2AU.dc:edo [o:~cisra\rc~rcO3148331 2AU.doceda -28- (vi) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image. A method according to claim 34, wherein step (ii) includes the sub-steps of: computing interpolation indicators for said second image based on said scaling factor; and calculating said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators.
  12. 36. The method according to claim 34, wherein the filter function is a cubic function.
  13. 37. The method according to claim 34, wherein the filter function is a linear function.
  14. 38. The method according to claim 34, wherein the filter function is a quadratic function.
  15. 39. The method according to claim 34, wherein the filter function is a weighted sinc function. The method according to claim 34, wherein said first image is a colour image.
  16. 41. The method according to claim 34, said method comprising the further step of convolving each pixel of said first image with said filter function.
  17. 42. The method according to claim 34, wherein said filter function is a one- dimensional function. CFP110AU RC03 (483312) [o:\dsra~rc~c03jAUspedi.doc: SaF CFP11O3AU R003 (483312) [o:\cisra\rc\rco3jAUspeci.doc:SaF -29-
  18. 43. The method according to claim 34, wherein said filter function is a two- dimensional functions.
  19. 44. The method according to claim 34, wherein a plurality of filter function coefficients are calculated simultaneously. An apparatus for performing interpolation on a pixel-based image, the apparatus comprising: calculator means for calculating a scaling factor of a first image compared to a second image, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; storage means for storing said filter function coefficients; detection means for detecting incoming pixels of said first image; coefficient access means for accessing said stored filter function coefficients; and interpolator for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  20. 46. The apparatus according to claim 45, wherein said calculator means computes interpolation indicators for said second image based on said scaling factor, and calculates said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators.
  21. 47. The apparatus according to claim 45, wherein the filter function is a cubic function.
  22. 48. The apparatus according to claim 45, wherein the filter function is a linear function. CFP110AU RC03 (483312) [o:\cisra\rc\rc03]AUsped.doc:SaF cFP11o3Au RCO3 (483312) [o:\cisra\rc\rcO3jAUspectdoc:SaF
  23. 49. The apparatus according to claim 45, wherein the filter function is a quadratic function. The apparatus according to claim 45, wherein the filter function is a weighted sinc function.
  24. 51. The apparatus according to claim 45, wherein said first image is a colour image.
  25. 52. The apparatus according to claim 45, said apparatus further comprising convolution means for convolving each pixel of said first image with said filter function.
  26. 53. The apparatus according to claims 45, wherein said filter function is a one- dimensional function.
  27. 54. The apparatus according to claim 45, wherein said filter function is a two- dimensional functions. The apparatus according to claim 45, wherein a plurality of filter function coefficients are calculated simultaneously.
  28. 56. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing interpolation on a pixel-based image, said program comprising: code for calculating a scaling factor of a first image compared to a second image, and calculating a plurality of filter function coefficients, based on said scaling factor, utilising one of a plurality of filter functions; code for storing said filter function coefficients; code for detecting incoming pixels of said first image; accessing said stored filter function coefficients; and CFP110AU RC03 (483312) lo:\cisra\rc\rc03)Auspeci.doc:SaF CFP11O3AU RCO3 (483312) [o:\cisra\rc\rcO3JAUspeci.doc:SaF -31 code for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  29. 57. The computer readable medium according to claim 56, said program further comprising: code for computing interpolation indicators for said second image based on said scaling factor; and code for calculating said plurality of filter function coefficients using said interpolation indicators, wherein a filter function coefficient is calculated for each of said interpolation indicators.
  30. 58. The computer readable medium according to claim 56, wherein the filter function is a cubic function.
  31. 59. The computer readable medium according to claim 56, wherein the filter furiction is a linear function. The computer readable medium according to claim 56, wherein the filter function is a quadratic function.
  32. 61. The computer readable medium according to claim 56, wherein the filter function is a weighted sinc function.
  33. 62. The computer readable medium according to claim 56, wherein said first image is a colour image.
  34. 63. The computer readable medium according to claim 56, said program further comprising code for convolving each pixel of said first image with said filter function. CFP1522AU RC03 (483312) [o:\dsrarcVW313483312AU.doc:edQ -32-
  35. 64. The computer readable medium according to claim 56, wherein said filter function is a one-dimensional function. The computer readable medium according to claims 56, wherein said filter function is a two-dimensional functions.
  36. 66. The computer readable medium according to claims 56, wherein a plurality of filter function coefficients are calculated simultaneously.
  37. 67. A method of performing interpolation on a pixel-based image, the method comprising the steps of: inputting dimension values of a first image and a second image: (ii) calculating a scaling factor of said first image compared to said second image; (iii) computing interpolation indicators for said second image based on' said scaling factor; (iv) calculating filter function coefficients, according to said interpolation indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; storing said filter function coefficients; (vi) detecting incoming pixels of said first image; and (vii) accessing said stored filter function coefficients; and (viii) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  38. 68. The method according to claim 67, wherein the filter function is a cubic function.
  39. 69. The method according to claim 67, wherein the filter function is a linear function. CFP1522AU RC03 (483312) [o:\cisra\rc~rd)3]483312AU.doc:edg -33- The method according to claim 67, wherein the filter function is a quadratic function.
  40. 71. The method according to claim 67, wherein the filter function is a weighted sinc function.
  41. 72. The method according to claim 67, wherein said first image is a colour image.
  42. 73. The method according to claim 67, said method comprising the further step of convolving each pixel of said first image with said filter function.
  43. 74. The method according to claim 67, wherein said filter function is a one- dimensional function.
  44. 75. The method according to claim 67, wherein said filter functions are two- dimensional functions.
  45. 76. The method according to claim 67, wherein a plurality of filter functions are calculated simultaneously.
  46. 77. An apparatus for performing interpolation on a pixel-based image, said apparatus comprising: input means for inputting dimension values of a first image and a second image: calculator means for calculating a scaling factor of said first image compared to said second image, computing interpolation indicators for said second image based on said scaling factor, and calculating filter function coefficients, according to said interpolation indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; storage means for storing said filter function coefficients; CFP110AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF -34- detection means for detecting incoming pixels of said first image; and coefficient access means for accessing said stored filter function coefficients; and interpolator for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  47. 78. The apparatus according to claim 77, wherein the filter function is a cubic function.
  48. 79. The apparatus according to claim 77, wherein the filter function is a linear function. The apparatus according to claim 77, wherein the filter function is a quadratic function.
  49. 81. The apparatus according to claim 77, wherein the filter function is a weighted sinc function.
  50. 82. The apparatus according to claim 77, wherein said first image is a colour image.
  51. 83. The apparatus according to claim 77, said apparatus further comprising convolution means for convolving each pixel of said first image with said filter function.
  52. 84. The apparatus according to claim 77, wherein said filter function is a one- dimensional function. The apparatus according to claim 77, wherein said filter functions are two- dimensional functions. CFP110AU RC03 (483312) [o:\cisra\rc\rc03]AUspeci.doc:SaF
  53. 86. The apparatus according to claim 77, wherein a plurality of filter functions are calculated simultaneously.
  54. 87. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing interpolation on a pixel-based image, said program comprising: code for inputting dimension values of a first image and a second image: code for calculating a scaling factor of said first image compared to said second image; code for computing interpolation indicators for said second image based on said scaling factor; code for calculating filter function coefficients, according to said interpolation indicators, utilising a filter function, wherein only those filter function coefficients required for said scaling factor are calculated; code for storing said filter function coefficients; code for detecting incoming pixels of said first image; and code for accessing said stored filter function coefficients; and code for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  55. 88. The computer readable medium according to claim 87, wherein the filter function is a cubic function.
  56. 89. The computer readable medium according to claim 87, wherein the filter function is a linear function. The computer readable medium according to claim 87, wherein the filter function is a quadratic function. CFP1103AU RC03 (483312) [o:rcisra\rc\rcO3]AUspeci.doc:SaF -36
  57. 91. The computer readable medium according to claim 87, wherein the filter function is a weighted sinc function.
  58. 92. The computer readable medium according to claim 87, wherein said first image is a colour image.
  59. 93. The computer readable medium according to claim 87, said method comprising the further step of convolving each pixel of said first image with said filter function.
  60. 94. The computer readable medium according to claim 87, wherein said filter function is a one-dimensional function. The computer readable medium according to claim 87, wherein said filter functions are two-dimensional functions.
  61. 96. The computer readable medium according to claim 87, wherein a plurality of filter functions are calculated simultaneously.
  62. 97. A method of performing image interpolation, the method comprising the steps: inputting dimension values of a first image and a second image; (ii) calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values; (iii) computing pairs of interpolation indicators according to said first and second sampling limit values; (iv) calculating fractional first and second coordinate values using said interpolation indicators; calculating filter function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; CFP1522AU RC03 (483312) ro:\cisa\rc\rvc031483312AU.doc:eda I a -37- (vi) storing said filter function coefficient values in a table; (vii) detecting input pixel values of said first image; (viii) accessing said stored filter function coefficients; and (ix) performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
  63. 98. An apparatus for performing image interpolation, the apparatus comprising: input means for inputting dimension values of a first image and a second image; calculator means for calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values, computing pairs of interpolation indicators according to said first and second sampling limit values, calculating fractional first and second coordinate values using said interpolation indicators, and calculating filter function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; storage means for storing said filter function coefficient values in a table; detection means for detecting input pixel values of said first image; coefficient access means for accessing said stored filter function coefficients; and interpolator for performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
  64. 99. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing image interpolation, said program comprising: code for inputting dimension values of a first image and a second image; code for calculating a first sampling increment value, a second sampling increment value, a first sampling limit value and a second sampling limit value, for said first image, using said dimension values; CFP110AU RC03 (483312) [o:\cisrarc\rc03]AUspeci.doc:SaF -38 code for computing pairs of interpolation indicators according to said first and second sampling limit values; code for calculating fractional first and second coordinate values using said interpolation indicators; code for calculating filter function coefficient values, based on said first and second fractional coordinate values, utilising a filter function; code for storing said filter function coefficient values in a table; detecting input pixel values of said first image; code for accessing said stored filter function coefficients; and code for performing image interpolation on said pixels of said first image using said stored filter function coefficient values to produce said second image.
  65. 100. A method of performing interpolation on a first pixel-based image, the method comprising the steps of: determining dimension values for a second image; (ii) calculating a plurality of filter function coefficients based on said dimension values; (iii) storing said filter function coefficients; (iv) detecting incoming pixels of said first image; accessing said stored filter function coefficients; and (vi) performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  66. 101. An apparatus for performing interpolation on a first pixel-based image, the method comprising the steps of: calculator means for determining means for determining dimension values for a second image and calculating a plurality of filter function coefficients based on said dimension values; storage means for storing said filter function coefficients; CFP1103AU RC03 (483312) [o:\cisra\rc\rcO3jAUspeci.doc:SaF -39- detection means for detecting incoming pixels of said first image; coefficient access means for accessing said stored filter function coefficients; and interpolator for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  67. 102. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of performing interpolation on a first pixel-based image, said program comprising: code for determining dimension values for a second image; code for calculating a plurality of filter function coefficients based on said dimension values; code for storing said filter function coefficients; code for detecting incoming pixels of said first image; code for accessing said stored filter function coefficients; and code for performing interpolation on said pixels of said first image, using said accessed filter function coefficients, to generate said second image.
  68. 103. A method of converting a first set of discrete data values to a second set of discrete data values, substantially as herein described with reference to the accompanying drawings.
  69. 104. An apparatus for converting a first set of discrete data values to a second set of discrete data values, substantially as herein described with reference to the accompanying drawings.
  70. 105. A computer readable medium for storing a program for an apparatus which processes data, said processing comprising a method of converting a first set of discrete data values to a second set of discrete data values, substantially as herein described with reference to the accompanying drawings. CFP11O3AU RC03 (483312) [o:\cisra\rc\rc03]Aspeci.doc: SaF DATED this thirteenth Day of December, 1999 Canon Kabushiki Kaisha Patent Attorneys for the Applicant/Nominated Person SPRUSON FERGUSON
AU65251/99A 1998-12-18 1999-12-15 Continuous kernel image interpolation Ceased AU730522B1 (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1990016035A2 (en) * 1989-06-16 1990-12-27 Eastman Kodak Company Digital image interpolator
WO1996016380A1 (en) * 1994-11-23 1996-05-30 Minnesota Mining And Manufacturing Company System and method for adaptive interpolation of image data
EP0908845A1 (en) * 1997-10-09 1999-04-14 Agfa-Gevaert N.V. Image sharpening and re-sampling method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1990016035A2 (en) * 1989-06-16 1990-12-27 Eastman Kodak Company Digital image interpolator
WO1996016380A1 (en) * 1994-11-23 1996-05-30 Minnesota Mining And Manufacturing Company System and method for adaptive interpolation of image data
EP0908845A1 (en) * 1997-10-09 1999-04-14 Agfa-Gevaert N.V. Image sharpening and re-sampling method

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