CN102646269A - Image processing method and device based on Laplace pyramid - Google Patents

Image processing method and device based on Laplace pyramid Download PDF

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CN102646269A
CN102646269A CN2012100493207A CN201210049320A CN102646269A CN 102646269 A CN102646269 A CN 102646269A CN 2012100493207 A CN2012100493207 A CN 2012100493207A CN 201210049320 A CN201210049320 A CN 201210049320A CN 102646269 A CN102646269 A CN 102646269A
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pyramid
image
gaussian
laplace
image processing
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CN102646269B (en
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李彦
王若梅
韩冠亚
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Sun Yat Sen University
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Abstract

The embodiment of the invention discloses an image processing method and device based on a Laplace pyramid, wherein the image processing method comprises the steps of: constructing a Gaussian pyramid corresponding to an input image; generating an intermediate image according to the Gaussian pyramid and a mapping function r(x); obtaining a coefficient of the Laplace pyramid according to the intermediate image; correspondingly outputting the coefficient of the Laplace pyramid based on the intermediate image to the Laplace pyramid until each point of the Laplace pyramid is filled, obtaining a new Laplace pyramid; and reconstructing an image according to the new Laplace pyramid, and obtaining an output image. By implementing the embodiment of the invention, the restraint that the traditional Laplace pyramid can not be used for carrying out edge preserving image enhancement, the edge preserving image enhancement is carried out by using the Laplace pyramid, the image processing method more simply and flexibly realizes image enhancement in comparison with the traditional edge preserving image enhancement methods (such as two-side filtering and wavelet methods), the time complexity can be reduced, and additional excessive parameters are not needed to be set.

Description

A kind of image processing method and device thereof based on laplacian pyramid
Technical field
The present invention relates to technical field of image processing, relate in particular to a kind of image processing method and device thereof based on laplacian pyramid.
Background technology
The figure image intensifying is an important application of computer technology; Its objective is and improve the visual effect of people to image, generalized case is the application scenario to given image, on purpose stresses the integral body or the local characteristics of image; With original unsharp image clear or emphasical some interested characteristic that becomes; Difference in the expanded view picture between the different objects characteristic suppresses uninterested characteristic, reaches the purpose of improving picture quality, abundant information amount; Strengthen image interpretation and recognition effect, satisfy the needs of some special analysis.
The method of figure image intensifying can be divided into two big types: frequency domain method and space domain method.Algorithm based on frequency domain is that the transform coefficient values to image carries out certain correction in certain transform domain of image, is a kind of algorithm of indirect enhancing; Directly image gray levels is done computing during based on the algorithm process in spatial domain.The former regards image as a kind of 2D signal, and it is carried out strengthening based on the signal of two-dimensional Fourier transform.Adopt LPF (promptly only letting low frequency signal pass through) method, can remove the noise among the figure; Adopt high-pass filtering method, then can strengthen high-frequency signals such as edge, make fuzzy picture become clear.The latter is divided into point processing algorithm and neighborhood Denoising Algorithm based on the algorithm in spatial domain.The point processing algorithm is gray level correction, greyscale transformation and histogram modification etc., and purpose is to make image imaging even, or enlarges dynamic range of images, expanded contrast.The neighborhood enhancement algorithms is divided into two kinds of image smoothing and sharpenings.Smoothly generally be used for the removal of images noise, but also cause the fuzzy of edge easily.Algorithms most in use has mean filter, medium filtering.The purpose of sharpening is the edge contour of outstanding object, is convenient to Target Recognition.Algorithms most in use has gradient method, operator, high-pass filtering, mask matching method, statistics differential technique etc.
In the prior art, though many methods can be used aspect image boundary, for example two-sided filter method, wavelet method etc.Bilateral filtering is a kind of wave filter that can protect the limit denoising, can reach this denoising effect and be because wave filter is to be made up of two functions, function be by geometric space apart from the decision filter coefficient, another determines filter coefficient by pixel value difference; Wavelet method is, and to serve as base with some special function be transformed to the characteristic of progression series with the similar frequency spectrum of finding it with data procedures or DS, thereby realize data processing.But these methods all relatively expend time in processing, and limit its practical ranges because of problems such as needs pre-treatment, quantity of parameters are provided with.
Summary of the invention
The objective of the invention is to overcome the deficiency of prior art; The invention provides a kind of image processing method and device thereof of laplacian pyramid; The constraint that traditional Laplace pyramid can not carry out edge maintenance figure image intensifying can be broken away from, the figure image intensifying can be realized more simply, more neatly.
In order to address the above problem, the present invention proposes a kind of image processing method based on laplacian pyramid, said method comprises:
The corresponding gaussian pyramid of structure input picture;
Generate intermediary's image according to said gaussian pyramid and mapping function r (x);
Obtain corresponding Laplce Laplace pyramid coefficient according to said intermediary image;
To output to accordingly on the Laplace pyramid based on the Laplace pyramid coefficient of said intermediary image, till pyramidal each point of said Lapalce all is filled, obtain new Laplace pyramid;
Based on said new Lapalce pyramid reconstructed image, and obtain output image.
Preferably, the said step that generates intermediary's image according to said gaussian pyramid and mapping function r (x) comprises: according to said gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
Preferably, said step according to said gaussian pyramid and mapping function r (x) generation intermediary image comprises:
Said input picture is carried out that detail signal is handled and the margin signal of said input picture is compressed.
Preferably, said structure input picture the step of corresponding gaussian pyramid comprise:
Construct the corresponding gaussian pyramid of image I of big or small w * h, wherein, gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).
Preferably, in said gaussian pyramid, each layer pyramid diagram picture is by the generation that reduces by half of the following wide and height of one deck pyramid diagram picture.
Correspondingly, the embodiment of the invention also provides a kind of image processing apparatus based on laplacian pyramid, and said image processing apparatus comprises:
Constructing module is used to construct the corresponding gaussian pyramid of input picture;
Generation module, the gaussian pyramid and the mapping function r (x) that are used for constructing according to said constructing module generate intermediary's image;
Coefficient obtains module, and the intermediary's image that is used for generating according to said generation module obtains corresponding Laplce Laplace pyramid coefficient;
The laplacian pyramid generation module is used for the Laplace pyramid coefficient based on said intermediary image is outputed to the Laplace pyramid accordingly, till pyramidal each point of said Lapalce all is filled, obtains new Laplace pyramid;
The image reconstruction module is used for the new Lapalce pyramid reconstructed image that generated according to said laplacian pyramid generation module, and obtains output image.
Preferably, said generation module also be used for according to said gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
Preferably, said generation module also is used for said input picture is carried out that detail signal is handled and the margin signal of said input picture is compressed.
Preferably, said constructing module also is used to construct the corresponding gaussian pyramid of image I of big or small w * h, wherein, and gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).
Preferably, in said gaussian pyramid, each layer pyramid diagram picture is by the generation that reduces by half of the following wide and height of one deck pyramid diagram picture.
The method of embodiment of the present invention embodiment; Can break away from the constraint that traditional Laplace pyramid can not carry out edge maintenance figure image intensifying; Utilizing the Laplace pyramid to carry out the edge keeps image to increase processing; Can keep image increase method (like bilateral filtering, wavelet method etc.) to realize the figure image intensifying more simply, more neatly than traditional edge, can reduce time complexity, extra mistake multiparameter need be set simultaneously.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art; To do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below; Obviously, the accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills; Under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is the schematic flow sheet based on the image processing method of laplacian pyramid of inventive embodiments;
Fig. 2 is that the signal of one dimension image in the embodiment of the invention is formed synoptic diagram;
Fig. 3 is that the one-dimensional signal of the image that use laplacian pyramid mode is constructed in the embodiment of the invention is formed synoptic diagram;
Fig. 4 is the principle of work synoptic diagram of the luminance compression of the embodiment of the invention;
Fig. 5 is that the structure based on the image processing apparatus of laplacian pyramid of the embodiment of the invention is formed synoptic diagram.
Embodiment
To combine the accompanying drawing in the embodiment of the invention below, the technical scheme in the embodiment of the invention is carried out clear, intactly description, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills are not making the every other embodiment that is obtained under the creative work prerequisite, all belong to the scope of the present invention's protection.
The present invention is based on Laplce (Laplace) pyramid and does edge maintenance figure image intensifying, so the Laplace pyramid is its core content, and the Laplace pyramid is based on gaussian pyramid (Gaussian Pyramid).In the Gaussian pyramid, the bottom is its original image, i.e. G 0=I, and each layer pyramid diagram picture all is the wide and high generation that reduces by half of one deck pyramid diagram picture down.And traditional Laplace pyramid is to enlarge the error image with next tomographic image by the last layer image through interpolation, its reflection be the information gap of gaussian pyramid two inter-stages, i.e. details.
The embodiment of the invention provides a kind of image processing method based on laplacian pyramid, and Fig. 1 is the schematic flow sheet based on the image processing method of laplacian pyramid of inventive embodiments, and as shown in Figure 1, this method comprises:
S101, the corresponding gaussian pyramid of structure input picture;
S102 generates intermediary's image according to input picture corresponding gaussian pyramid of institute and mapping function r (x);
S103 obtains corresponding Laplce Laplace pyramid coefficient according to intermediary's image;
S104 will output on the Laplace pyramid based on the Laplace pyramid coefficient of intermediary's image accordingly, till pyramidal each point of Lapalce all is filled, obtains new Laplace pyramid;
S105 based on new Lapalce pyramid reconstructed image, and obtains output image.
In practical implementation, be the image I of w * h to size, in S101, can construct the corresponding gaussian pyramid of image I of big or small w * h, wherein, gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).
Wherein, 102 further comprise: according to gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
About mapping function r, wherein, input parameter σ rBe the threshold values that is used to distinguish border and texture, promptly the grey scale change in certain vertex neighborhood is less than or equal to σ rThe time, then think texture, when greater than σ rShi Ze thinks the border.And g 0It then is the expectation pixel value of this point of surface.When the some variation range in the neighborhood all is not more than the threshold value on border, can think that this point is in texture region; Otherwise, then be illustrated in boundary vicinity.To these two kinds of condition of different, the form of mapping function r is different.But no argument is in what zone, and mapping function r should be a monotonically increasing, to guarantee the situation that gray scale reverses not occur.Further, in order to guarantee the continuity of gradation of image, be in which zone no matter be positioned at the point at threshold value place, the functional value after their mappings should equate.
In the practical implementation, when generating intermediary's image, on the one hand input picture is carried out detail signal and handle, the margin signal to input picture compresses on the other hand, just will block original signal this pixel value and g in certain neighborhood 0Difference on codomain is greater than σ rValue.
In the practical implementation process, can the said method process be applied to the color space, only need r in the following formula and g are changed to vector, absolute value changes vector norm into, and sign function changes following unit function into and gets final product.
unit ( v → ) = v → | | v → | |
In image processing process, generally all be to analyze the one dimension image earlier, expand to analysis again to coloured image.
When analyzing the signal (one-dimensional signal) of one dimension image; Analyze the composition of one-dimensional signal earlier, one-dimensional signal I is made up of three parts, margin signal E, the slow signal S of variation, high-frequency signal D; Specifically as shown in Figure 2; Margin signal E is typical step function, and the average of high-frequency signal D is zero, and the gradient magnitude on the every bit all will be much smaller than ladder amplitude of variation among the E.Change the low frequency component in the slow signal S representation signal, for example the slow increase or the minimizing of signal intensity.For the regional area of image, the every bit in the signal can be expressed as the linear combination of above-mentioned 3 signals, and just different local, the coefficient of each component is inequality.
Construct ground floor L when using the pyramidal mode of Laplace 0, second layer L 1, the 3rd layer of L 2Deng, in whole Laplace pyramid, the situation of one-dimensional signal is as shown in Figure 3, can be drawn by Fig. 3:
(1) pyramidal progression is high more, and the high frequency details just fades away;
(2) pyramidal progression is high more, and picture size is more and more littler, and the change frequency of otherwise smooth can raise, and produces high-frequency signal;
(3) composition does not reduce along with the raising of level, and this explanation border in the figure of low resolution still can be confirmed.
Can find out that from the analysis content of front it is details or edge that laplace coefficient can be taken as, the edge amplitude is far longer than the amplitude of details, therefore can pass through parameter σ rDistinguish border and texture.
The method of the embodiment of the invention can be applied in figure image intensifying aspects such as details enhancing, tone map, in concrete application process, different parameters need be set.Aspect tone map, can adopt the method for luminance compression.Luminance compression can realize D+E → D+E ', and wherein D is a detail signal, and E is a margin signal, and E ' is the margin signal after changing, promptly same detail section, and the marginal portion reduces, and in the practical implementation is to compress margin signal, and margin signal is changed.The principle of work of luminance compression is as shown in Figure 4, can be known by Fig. 4, and the signal after the processing is compared with original signal, and the amplitude of margin signal has reduced, but owing to do not change detail signal, so the character of signal remains unchanged.
The luminance compression specific operation process is: export signal and be set to I ', the image sequence that its each layer of Laplace image pyramid formed then is designated as { L [I '] }.Can be easy to rebuild by { L [I '] } and feed back out signal.The pixel value of any in { L [I '] } on a certain image is by the position x of pixel 0With image place layer decision L 0(L 0Be the bottom of laplacian pyramid, the difference after just the gaussian pyramid ground floor and the second layer double obtains).Pixel value with one deck same point in the Gaussian image pyramid is set to g 0The figure of the intermediary layer Laplace pyramid of constructing in the said method of the embodiment of the invention will block original signal this pixel value and g in certain neighborhood 0Distance on codomain is greater than σ rValue, promptly have
T=min [max (I, g 0-σ r), g 0+ σ r], can realize the tone map of image through above-mentioned luminance compression method.
The method of embodiment of the present invention embodiment; Can break away from the constraint that traditional Laplace pyramid can not carry out edge maintenance figure image intensifying; Utilizing the Laplace pyramid to carry out the edge keeps image to increase processing; Can keep image increase method (like bilateral filtering, wavelet method etc.) to realize the figure image intensifying more simply, more neatly than traditional edge, can reduce time complexity, extra mistake multiparameter need be set simultaneously.
The embodiment of the invention also provides a kind of image processing apparatus based on laplacian pyramid, and Fig. 5 is that the structure based on the image processing apparatus of laplacian pyramid of the embodiment of the invention is formed synoptic diagram, and as shown in Figure 5, this image processing apparatus comprises:
Constructing module 50 is used to construct the corresponding gaussian pyramid of input picture;
Generation module 51, the gaussian pyramid and the mapping function r (x) that are used for being constructed according to constructing module 50 generate intermediary's image;
Coefficient obtains module 52, is used for obtaining corresponding Laplce Laplace pyramid coefficient according to intermediary's image that generation module 51 is generated;
Laplacian pyramid generation module 53 is used for the Laplace pyramid coefficient based on intermediary's image is outputed to the Laplace pyramid accordingly, till pyramidal each point of Lapalce all is filled, obtains new Laplace pyramid;
Image reconstruction module 54 is used for the new Lapalce pyramid reconstructed image that generated according to the laplacian pyramid generation module, and obtains output image.
In the practical implementation, in practical implementation, be the image I of w * h, can construct the corresponding gaussian pyramid of image I of big or small w * h through constructing module 50 to size, wherein, gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).Wherein, generation module 51 also be used for according to gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
Generation module 51 also is used for input picture is carried out that detail signal is handled and the margin signal of input picture is compressed.
Can describe referring to the respective process among the embodiment of the image processing method based on laplacian pyramid of the present invention based on the implementation procedure of each functions of modules of the image processing apparatus of laplacian pyramid and principle among apparatus of the present invention embodiment repeated no more here.
In apparatus of the present invention embodiment; Utilizing the Laplace pyramid to carry out the edge keeps image to increase processing; Can break away from the constraint that traditional Laplace pyramid can not carry out edge maintenance figure image intensifying; Can keep image increase method (like bilateral filtering, wavelet method etc.) to realize the figure image intensifying more simply, more neatly than traditional edge, can reduce time complexity, extra mistake multiparameter need be set simultaneously.
One of ordinary skill in the art will appreciate that all or part of step in the whole bag of tricks of the foregoing description is to instruct relevant hardware to accomplish through program; This program can be stored in the computer-readable recording medium; Storage medium can comprise: ROM (read-only memory) (Read Only Memory; ROM), RAS (Random Access Memory, RAM), disk or CD etc.
In addition; More than the image processing method and the device thereof of the laplacian pyramid that the embodiment of the invention provided is described in detail; Used specific case herein principle of the present invention and embodiment are set forth, the explanation of above embodiment just is used for helping to understand method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, the part that all can change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.

Claims (10)

1. the image processing method based on laplacian pyramid is characterized in that, said method comprises:
The corresponding gaussian pyramid of structure input picture;
Generate intermediary's image according to said gaussian pyramid and mapping function r (x);
Obtain corresponding Laplce Laplace pyramid coefficient according to said intermediary image;
To output to accordingly on the Laplace pyramid based on the Laplace pyramid coefficient of said intermediary image, till pyramidal each point of said Lapalce all is filled, obtain new Laplace pyramid;
Based on said new Lapalce pyramid reconstructed image, and obtain output image.
2. the image processing method based on laplacian pyramid as claimed in claim 1 is characterized in that, the said step that generates intermediary's image according to said gaussian pyramid and mapping function r (x) comprises: according to said gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
3. according to claim 1 or claim 2 the image processing method based on laplacian pyramid is characterized in that, the said step that generates intermediary's image according to said gaussian pyramid and mapping function r (x) comprises:
Said input picture is carried out that detail signal is handled and the margin signal of said input picture is compressed.
4. the image processing method based on laplacian pyramid as claimed in claim 1 is characterized in that, said structure input picture the step of corresponding gaussian pyramid comprise:
Construct the corresponding gaussian pyramid of image I of big or small w * h, wherein, gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).
5. the image processing method based on laplacian pyramid as claimed in claim 4 is characterized in that, in said gaussian pyramid, each layer pyramid diagram picture is by the generation that reduces by half of the following wide and height of one deck pyramid diagram picture.
6. the image processing apparatus based on laplacian pyramid is characterized in that, said image processing apparatus comprises:
Constructing module is used to construct the corresponding gaussian pyramid of input picture;
Generation module, the gaussian pyramid and the mapping function r (x) that are used for constructing according to said constructing module generate intermediary's image;
Coefficient obtains module, and the intermediary's image that is used for generating according to said generation module obtains corresponding Laplce Laplace pyramid coefficient;
The laplacian pyramid generation module is used for the Laplace pyramid coefficient based on said intermediary image is outputed to the Laplace pyramid accordingly, till pyramidal each point of said Lapalce all is filled, obtains new Laplace pyramid;
The image reconstruction module is used for the new Lapalce pyramid reconstructed image that generated according to said laplacian pyramid generation module, and obtains output image.
7. the image processing apparatus based on laplacian pyramid as claimed in claim 6 is characterized in that, said generation module also be used for according to said gaussian pyramid and
r ( i ) = g 0 + sign ( i - g 0 ) σ r f d ( i a ) , | i - g 0 | ≤ σ g 0 + sign ( i - g 0 ) [ f e ( | i - g 0 | - σ r ) + σ r ] , otherwise
Generate intermediary's image;
Wherein, parameter σ rBe the threshold values that is used to distinguish border and texture, g 0Be the expectation pixel value of this point of surface, function f is that [0,1] interval is mapped to [0,1] interval smooth function, f dThe expression details strengthens function, f eThe expression tone strengthens function, and i is the original pixel value of this point, | i-g 0| be the grey scale change in this field, a changes the degree that the adjustment details is strengthened.
8. like claim 6 or 7 described image processing apparatus, it is characterized in that said generation module also is used for said input picture is carried out that detail signal is handled and the margin signal of said input picture is compressed based on laplacian pyramid.
9. the image processing apparatus based on laplacian pyramid as claimed in claim 6 is characterized in that, said constructing module also is used to construct the corresponding gaussian pyramid of image I of big or small w * h, wherein, and gaussian pyramid G iThe gaussian image I that reduces by the resolution of I iForm, i represents the progression of gaussian pyramid, i={0, and 1 ..., j}, image I iSize be (w/2 i) * (h/2 i).
10. the image processing apparatus based on laplacian pyramid as claimed in claim 9 is characterized in that, in said gaussian pyramid, each layer pyramid diagram picture is by the generation that reduces by half of the following wide and height of one deck pyramid diagram picture.
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