US20090278957A1 - Image processing apparatus, method, and program - Google Patents

Image processing apparatus, method, and program Download PDF

Info

Publication number
US20090278957A1
US20090278957A1 US12/434,871 US43487109A US2009278957A1 US 20090278957 A1 US20090278957 A1 US 20090278957A1 US 43487109 A US43487109 A US 43487109A US 2009278957 A1 US2009278957 A1 US 2009278957A1
Authority
US
United States
Prior art keywords
image
gain
pixel
low frequency
processing target
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US12/434,871
Other languages
English (en)
Inventor
Seiji Tanaka
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fujifilm Corp
Original Assignee
Fujifilm Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fujifilm Corp filed Critical Fujifilm Corp
Assigned to FUJIFILM CORPORATION reassignment FUJIFILM CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TANAKA, SEIJI
Publication of US20090278957A1 publication Critical patent/US20090278957A1/en
Priority to US13/471,016 priority Critical patent/US8345121B2/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/136—Segmentation; Edge detection involving thresholding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform

Definitions

  • the present invention relates to an image processing method and apparatus for compressing the dynamic range of an image by changing the gain of the image.
  • the invention also relates to a computer readable recording medium on which is recorded a program for causing a computer to perform the image processing method.
  • a dynamic range compression method is proposed.
  • the method generates a low frequency image of an image and reduces the contrast of a high luminance region, a low luminance region, or the entire image such that the difference between the maximum luminance value and minimum luminance value, i.e., dynamic range is reduced using the low frequency image. More specifically, a low frequency image of an image is generated, then a gain is calculated from the low frequency image such that the darker (i.e., the lower the luminance value) the low frequency image the higher the gain, and the calculated gain is added to each pixel or each pixel is multiplied by the gain.
  • the dynamic range compression allows for making a bright region of an image darker and a dark region of the image brighter.
  • a high contrast image of a person taken against light can be turned into a high quality image by correcting halation in the background and dark collapsed person's face.
  • the method described in Patent Document 1 compresses the dynamic range of an image by generating a plurality of band-limited image signals of different frequency bands from an image signal representing the image, generating a cumulative signal by integrating the band-limited image signals in which some of them are reduced before integrated, converting a differential signal obtained by subtracting the cumulative signal from the image signal of the original image by a predetermined function, and adding the signal obtained by the conversion to the original image.
  • the method described in Patent Document 2 is a method that calculates a correction value for dynamic range compression by making comparison in magnitude of pixel value between an image and a low frequency image thereof.
  • Patent Document 1 is not able to completely eliminate overshooting or undershooting adjacent to an edge included in an image, since the dynamic range compression is performed based on frequency separation of the image.
  • the method described in Patent Document 2 may cause a processed image to be discontinuous at a position where the correction value is changed, since the correction value is calculated based on the magnitude of pixel value between an image and a low frequency image thereof.
  • the present invention has been developed in view of the circumstances described above, and it is an object of the present invention to improve image quality of a dynamic range compressed image.
  • a first image processing apparatus of the present invention is an apparatus, including:
  • a region setting unit for setting one or more regions on a processing target image in which each pixel of the image is included according to a level of each pixel;
  • a low frequency image generation unit for generating a low frequency image of the processing target image
  • a gain calculation unit for calculating a gain for each pixel of the processing target image such that the lower the level the greater the gain, wherein the unit calculates the gain such that pixels in each of the one or more regions in which each pixel of the processing target image is included have substantially the same gain based on a region setting result and a level of each pixel of the low frequency image;
  • a processing unit for generating a processed image by performing dynamic range compression on the processing target image based on the gain.
  • the gain calculation unit may be a unit that calculates a provisional gain for each pixel of the low frequency image such that the lower the level the greater the gain and, based on the region setting result, calculates a representative value of the provisional gains of pixels in each of the one or more regions in which each pixel of the processing target image is included as the gain for each pixel of the processing target image.
  • the average value, weighted average value, or intermediate value of the provisional gains, or the like may be used.
  • the gain calculation unit may be a unit that calculates, based on the region setting result, a representative value of pixels in each of the one or more regions in which each pixel of the low frequency image is included, and calculates the gain for each pixel of the processing target image such that the lower the level of the representative value the greater the gain.
  • the average value, weighted average value, or intermediate value of the pixels, or the like may be used.
  • a second image processing apparatus of the present invention is an apparatus, including:
  • a low frequency image generation unit for generating a plurality of low frequency images of different frequency bands from a processing target image
  • a region setting unit for setting one or more regions on at least one of those of the plurality of low frequency images up to a predetermined frequency band, which is higher than a first frequency band, in which each pixel of the at least one low frequency image is included according to a level of each pixel of the at least one low frequency image;
  • a gain calculation unit for calculating a first gain for each pixel of a first low frequency image of the first frequency band such that the lower the level the greater the gain, calculating, based on a region setting result, a representative value of the first gains of pixels in each of the one or more regions in which each pixel of a second low frequency image of a second frequency band, which is next higher than the first frequency band, is included as a second gain of each pixel of the second low frequency image, and outputting a second gain calculated by repeating the calculation of a new second gain using a low frequency image of the next higher frequency band than that of the second low frequency image as a new second low frequency image and the second gain as a new first gain to the predetermined frequency band as a final gain of each pixel of the processing target image; and
  • a processing unit for generating a processed image by performing dynamic range compression on the processing target image based on the gain.
  • a photographing apparatus of the present invention is an apparatus, including:
  • an imaging unit for obtaining a processing target image by photographing a subject
  • a first image processing method of the present invention is a method including the steps of:
  • a second image processing method of the present invention is a method including the steps of:
  • Each of the first and second image processing methods of the present invention may be provided as a program recorded on a computer readable recording medium for causing a computer to perform the method.
  • one or more regions is set on a processing target image in which each pixel of the image is included according to a level of each pixel, and further a low frequency image of the processing target image is generated. Then, based on a region setting result and a level of each pixel of the low frequency image, the gain is calculated such that pixels in each of the one or more regions in which each pixel of the processing target image is included have substantially the same gain, and based on the calculated gain, a processed image is generated by performing dynamic range compression on the processing target image.
  • substantially the same gain is calculated for pixels in each of the one or more regions of the processing target image in which each pixel of the processing target image is included. Consequently, dynamic range compression of the processing target image does not cause overshooting and undershooting arising from a large pixel value variation adjacent to the boundary of the one or more regions in which each pixel of the image is included. Therefore, a high quality processed image without overshooting and undershooting may be obtained.
  • the low frequency image represents a brightness variation of the processing target image in a manner such that the lower the frequency band of the low frequency image, the more global will be the variation. Therefore, in order to calculate the gain for changing an overall dynamic range of the processing target image, it is preferable that the frequency band of the low frequency image is as low as possible.
  • the frequency difference between the two images becomes large, and the blurred range, i.e., variation range of pixel levels in the low frequency image becomes very large at the boundary between the regions in which each pixel of the processing target image is included, so that the use of the region setting result of the processing target image does not yield appropriate gains.
  • a plurality of low frequency images of different frequency bands is generated from a processing target image, and one or more regions are set on at least one of those of the plurality of low frequency images up to a predetermined frequency band, which is higher than a first frequency band, in which each pixel of the at least one low frequency image is included according to a level of each pixel of the at least one low frequency image.
  • a first gain is calculated such that the lower the level of each pixel of a first low frequency image of the first frequency band the greater the gain and, based on a region setting result, a representative value of the first gains of pixels in each of the one or more regions in which each pixel of a second low frequency image of a second frequency band, which is next higher than the first frequency band, is included is calculated as a second gain of each pixel of the second low frequency image.
  • the first and second low frequency images are close to each other in frequency band, so that the difference in blur degree is small. Therefore, the pixel level variation range in the first low frequency image becomes small at the boundary between the regions in which each pixel of the second low frequency image is included, so that the gains for the second low frequency image may be calculated appropriately.
  • the calculation of a new second gain is repeated using a low frequency image of the next higher frequency band than that of the second low frequency image as a new second low frequency image and the second gain as a new first gain to the predetermined frequency band, and a second gain calculated by this is outputted as a final gain of each pixel of the processing target image.
  • the gain according to a global brightness variation of the processing target image may be calculated without being influenced by the variation range of pixel levels at the boundary between the regions in which each pixel of the processing target image is included. Accordingly, a high quality processed image without overshooting and undershooting may be obtained.
  • FIG. 1 is a schematic block diagram of a digital camera to which the image processing apparatus according to a first embodiment of the present invention is applied, schematically illustrating the configuration thereof.
  • FIG. 2 illustrates a configuration of the imaging unit shown in FIG. 1 .
  • FIG. 3 illustrates an example of a color filter.
  • FIG. 4 is a schematic block diagram of the gain processing unit shown in FIG. 1 , schematically illustrating the configuration thereof.
  • FIG. 5 is a two-dimensional representation of the luminance values of an image for explaining gain calculation.
  • FIG. 6 is a two-dimensional representation of the luminance values of a blurred image for explaining gain calculation.
  • FIG. 7 illustrates a luminance value curve of an edge portion for explaining gain calculation.
  • FIG. 8 illustrates a provisional gain curve
  • FIG. 9 illustrates the state in which overshooting and undershooting occur.
  • FIG. 10 is a two-dimensional representation of the provisional gains calculated based on the blurred image.
  • FIG. 11 is a two-dimensional representation of the final gains calculated based on the region setting result.
  • FIG. 12 illustrates provisional and final gain curves.
  • FIG. 13 illustrates a gain processing result according to the first embodiment.
  • FIG. 14 is a flowchart illustrating processing performed in the first embodiment.
  • FIG. 15 schematically illustrates processing performed in a second embodiment.
  • FIG. 16 is a flowchart illustrating the processing performed in the second embodiment.
  • FIG. 17 illustrates region setting of a blurred image.
  • FIG. 1 is a schematic block diagram of a digital camera to which the image processing apparatus according to a first embodiment of the present invention is applied, illustrating the configuration thereof.
  • digital camera 1 according to the present embodiment includes imaging unit 2 , imaging control unit 3 , signal processing unit 4 , compression/expansion unit 5 , frame memory 6 , medium control unit 7 , internal memory 8 , and display control unit 9 .
  • FIG. 2 illustrates a configuration of imaging unit 2 .
  • imaging unit 2 includes lens 20 , aperture 21 , shutter 22 , CCD 23 , analog front-end (AFE) 24 , and A/D converter 25 .
  • AFE analog front-end
  • Lens 20 includes a plurality of functional lenses, such as a focus lens for bringing a subject into focus, a zoom lens for realizing a zoom function and the like, and positions of the lenses are controlled by a not shown lens drive unit.
  • the aperture diameter of aperture 21 is controlled by a not shown aperture drive unit based on the aperture data obtained by AE processing.
  • Shutter 22 is a mechanical shutter and driven by a not shown shutter drive unit according to the shutter speed obtained by AE processing.
  • CCD 23 includes a photoelectric surface having multitudes of light receiving elements disposed two-dimensionally, and a light image representing a subject is formed on the photoelectric surface and subjected to photoelectric conversion, whereby an analog image signal is obtained.
  • a color filter having R, G, and B filters disposed regularly is provided in front of CCD 23 .
  • AFE performs noise reduction and gain adjustment (hereinafter, analog processing) on an analog image signal outputted from CCD 23 .
  • A/D conversion unit 25 converts the analog image signal analog-processed by AFE to a digital signal.
  • the image data obtained by converting the analog image signal obtained by CCD 23 of imaging units 2 are RAW data in which each pixel has a density value of R, G, or B.
  • Imaging control unit 3 controls imaging after the release button is depressed. It also performs AF and AE processing to set the focal position, aperture value data and shutter speed when the release button is depressed half-way. When the release button is not depressed, imaging control unit 3 controls imaging unit 2 to take a through image.
  • Signal processing unit 4 performs signal processing, such as white balance correction, tone correction, sharpness correction, and color correction on the digital image data obtained by imaging unit 2 .
  • Compression/expansion unit 5 generates an image file by compressing the image data processed by signal processing unit 4 , for example, in JPEG compression format.
  • Frame memory 6 is a work memory used when various types of processing, including the processing of signal processing unit 4 , are performed on the image data representing the image obtained by imaging units 2 .
  • Medium control unit 7 gains access to recording medium 10 and controls read/write operations of image file.
  • Internal memory 8 has stored therein various constants to be set in digital camera 1 , programs to be executed by CPU 13 , and the like.
  • Display control unit 9 causes image data stored in frame memory 6 or an image recorded in recording medium 10 to be displayed on monitor 11 .
  • Digital camera 1 further includes gain processing unit 12 .
  • FIG. 4 is a schematic block diagram of gain processing unit 12 , illustrating the configuration thereof. As illustrated in FIG. 4 , gain processing unit 12 includes level information calculation unit 31 , low frequency image generation unit 32 , region setting unit 33 , gain calculation unit 34 , and multiplication unit 35 .
  • Level information calculation unit 31 calculates the level of each pixel of processing target image S 0 (hereinafter, also simply referred to as “image S 0 ”) obtained by photographing and not yet subjected to the signal processing. More specifically, level information calculation unit 31 calculates luminance value Y of each pixel as the level by Formula (1) below.
  • each pixel of image S 0 has only one of R G B values, so that level information calculation unit 31 calculates luminance value Y of each pixel after calculating each of RGB values by performing interpolation operations using RGB values of surrounding pixels. More specifically, for a pixel having a R value shown in FIG. 3 , level information calculation unit 31 calculates G and B values by performing interpolation operations using G values of four adjacent pixels in the left/right and up/down directions and B values of four adjacent pixels in the directions diagonal to the left/right and up/down directions.
  • For a pixel having a B value it calculates G and R values by performing interpolation operations using G values of four adjacent pixels in the left/right and up/down directions and R values of four adjacent pixels in the directions diagonal to the left/right and up/down directions. For a pixel having a G value, it calculates R and B values by performing interpolation operations using R values of two adjacent pixels in the left/right or up/down direction and B values of two adjacent pixels in the left/right or up/down direction.
  • Low frequency image generation unit 32 generates blurred image Sus 0 by filtering image S 0 constituted by luminance values Y using a low-pass filter.
  • Region setting unit 33 sets one or more regions on image S 0 in which each pixel of image S 0 is included according to the magnitude of luminance value Y of each pixel. More specifically, region setting unit 33 calculates, with respect to each region setting target pixel of image S 0 , an absolute value of difference between luminance value Y of the target pixel and luminance value Y of another pixel in a predetermined range surrounding the target pixel, and sets an region formed of pixels whose absolute values of difference are within a predetermined threshold value Th 1 as the region in which the target pixel is included.
  • each of luminance values Y in the upper right region is 255 and each of luminance values Y in lower left region is 1, and if the shaded pixel in the center is the region setting target pixel, the region in which the target pixel is included is the upper right region formed of pixels having luminance value Y of 255, since the luminance value Y of 255 is the same value as that of the target pixel.
  • the luminance value Y of 1 differs largely from that of the target pixel, so that the target pixel does not belong to the lower left region.
  • luminance values Y of the boundary area are reduced in the upper right region and increased in the lower left region, whereby the boundary is blurred.
  • Gain calculation unit 34 calculates provisional gains Gk based on blurred image Sus 0 such that the darker the portion of image S 0 having smaller luminance value Y, the greater the provisional gain. For example, with respect to an edge portion of image So shown in FIG. 7 , the variation of luminance values Y becomes smooth in blurred image Sus 0 , as shown by a dashed line in FIG. 7 , so that gain calculation unit 34 calculates smoothly varying provisional gains Gk such that the greater the luminance value of blurred image Sus 0 the greater the provisional gain, as shown in FIG. 8 .
  • the dynamic range i.e., contrast of image So may be reduced, so that a high contrast image of a person taken against light can be turned into a high quality image by correcting halation in the background and dark collapsed person's face.
  • a representative value of provisional gains Gk for pixels in each of the one or more regions of image S 0 in which each pixel of image S 0 is included is calculated as final gain Gf based on a region setting result. For example, as shown in FIG. 10 , where provisional gain Gk for each pixel in the boundary area in the upper right region is 0.3 and provisional gain Gk for each of the other pixels in the upper right region is 0.5, and provisional gain Gk for each pixel in the boundary area in the lower left region is 5 and provisional gain Gk for each of the other pixels in the lower left region is 10, the average value of provisional gains Gk of all pixels in the upper right region is calculated as final gain Gf for the target pixel in the center.
  • the average value of provisional gains Gk of all pixels is calculated as final gain Gf. This will result in that gain Gf for each pixel in the upper right region is 0.43 and gain Gf for each pixel in the lower left region is 5.8, as shown in FIG. 11 .
  • final gains Gf are calculated such that the gain variation in the boundary area becomes steeper than that of provisional gains Gk, as shown in FIG. 12 . Accordingly, if dynamic range compression is performed on image So using final gains Gf, overshooting or undershooting is prevented adjacent to an edge in image So, as shown in FIG. 13 .
  • CPU 13 controls each unit of digital camera 1 according to a signal from input/output unit 14 that includes an arrow key, various operation buttons, and the release button.
  • Data bus 15 connects each unit of digital camera 1 and CPU 13 , and various types of data and information in digital camera 1 are exchanged through the bus.
  • FIG. 14 is a flowchart illustrating the processing performed in the first embodiment.
  • level information calculation unit 31 of gain processing unit 12 calculates the level of each pixel of image S 0 (step ST 1 ).
  • low frequency image generation unit 32 generates blurred image Sus 0 of image S 0 (step ST 2 )
  • region setting unit 33 sets one or more regions on image S 0 in which each pixel of image S 0 is included according to the level of each pixel (step ST 3 ).
  • gain calculation unit 34 calculates provisional gains Gk according to blurred image Sus 0 (step ST 4 ) and calculates final gains Gf based on a region setting result (step ST 5 ).
  • Multiplication unit 35 compresses the dynamic range of image S 0 by multiplying each pixel of image S 0 by gain Gf, thereby generating dynamic range compressed image S 1 (step ST 6 ).
  • signal processing unit 4 performs signal processing on dynamic range compressed image S 1 , thereby generating processed image S 2 (step ST 7 ). Then, compression/expansion unit 5 generates an image file (step ST 8 ) and medium control unit 7 records the image file on recording medium 10 (step ST 9 ), thereby terminating the processing.
  • one or more regions are set on image S 0 in which each pixel of image S 0 is included according to the level of each pixel of image S 0 , whereby a substantially the same gain is calculated for each pixel in each of the one or more regions. Consequently, dynamic range compression of image S 0 does not cause overshooting and undershooting arising from a large pixel value variation adjacent to the boundary of the one or more regions in which each pixel of image S 0 is included. Therefore, high quality processed image S 2 without overshooting and undershooting may be obtained.
  • the configuration of a digital camera having an image processing apparatus according to the second embodiment is identical to that of the digital camera having the image processing apparatus according to the first embodiment, so that it will not be elaborated upon further here.
  • the second embodiment differs from the first embodiment only in the processing performed by gain processing unit 12 .
  • the second embodiment differs from the first embodiment in that, in the first embodiment, only one blurred image is generated, while in the second embodiment, a plurality of blurred images of different frequency bands is generated.
  • FIG. 15 schematically illustrates processing performed in the second embodiment.
  • low frequency image generation unit 32 generates a plurality of blurred images Sus 0 to Susn of different frequency bands from image S 0 constituted by luminance values Y in the second embodiment. More specifically, low frequency image generation unit 32 generates a plurality of blurred images Sus 0 to Susn by filtering image S 0 repeatedly using low-pass filters or by performing a multiple resolution conversion by wavelet transform or the like.
  • “n” represents the number of blurred images and the greater the “n” the higher the frequency band of the blurred image.
  • region setting unit 33 sets one or more regions on each of blurred images Sus 1 to Susn in which each pixel is included.
  • gain calculation unit 34 calculates provisional gains G 0 based on blurred image Sus 0 of the lowest frequency band in the same manner as in the first embodiment. Then, based on a region setting result of blurred image Sus 1 of the next higher frequency band than that of blurred image Sus 0 , gain calculation unit 34 calculates a representative value of provisional gains G 0 of pixels in each of the one or more regions of blurred image Sus 1 as provisional gain G 1 of blurred image Sus 1 .
  • the calculation of provisional gains G 1 is performed in the same manner as the calculation of provisional gains Gk based on blurred image Sus 0 and final gain Gf based on the region setting result of image S 0 in the first embodiment.
  • gain calculation unit 34 calculates a representative value of provisional gains G 1 of pixels in each of the one or more regions of blurred image Sus 2 as provisional gains G 2 of blurred image Sus 2 .
  • gain calculation unit 34 repeats the calculation until provisional gains Gn for blurred image Susn of a highest frequency band is calculated and outputs provisional gains Gn as final gains Gf.
  • FIG. 16 is a flowchart illustrating processing performed in the second embodiment.
  • processing after an instruction to start photographing is issued by a full depression of the release button and digital image S 0 is generated will be described.
  • image S 0 is obtained by photographing
  • level information calculation unit 31 of gain processing unit 12 calculates the level of each pixel of image S 0 (step ST 11 ).
  • low frequency image generation unit 32 generates a plurality of blurred images Sus 0 to Susn from image S 0 (step ST 12 ), and region setting unit 33 sets one or more regions on each of images Sus 1 to Susn, other than blurred image Sus 0 of a lowest frequency band, in which each pixel of each of blurred images Sus 1 to Susn is included according to the level of each pixel (step ST 13 ).
  • step ST 17 If step ST 17 is positive, multiplying unit 25 compresses the dynamic range of image S 0 by multiplying each pixel of image S 0 by final gain Gf (Gn), thereby generating dynamic range compressed image S 1 (step ST 19 ).
  • signal processing unit 4 performs signal processing on dynamic range compressed image Sl, thereby generating processed image S 2 (step ST 20 ). Then, compression/expansion unit 5 generates an image file (step ST 21 ) and medium control unit 7 records the image file on recording medium 10 (step ST 22 ), thereby terminating the processing.
  • blurred image Sus 0 represents a brightness variation of image S 0 in a manner such that the lower the frequency band of blurred image Sus 0 , the more global will be the variation. Therefore, in order to calculate the gain for changing an overall dynamic range of image S 0 , it is preferable that the frequency band of blurred image Sus 0 is as low as possible.
  • blurred image Sus 0 has a very low frequency band in comparison with that of original image S 0 , the frequency difference between the two images becomes large, and the blurred range, i.e., level variation range in blurred image Sus 0 becomes very large at the boundary between the one or more regions in which each pixel of image S 0 is included, so that the use of the region setting result of image S 0 does not yield appropriate gains.
  • a plurality of blurred images Sus 0 to Susn of different frequency bands is generated from image S 0 , and according to the level of each pixel of each of blurred images Sus 1 to Susn having higher frequency bands than a lowest frequency band of the plurality of blurred images, one or more regions is set on each of blurred images Sus 1 to Susn in which each pixel is included. Then, from provisional gains G 0 calculated based on blurred image Sus 0 having a lowest frequency band, provisional gains G 1 is calculated based on the region setting result of blurred image Sus 1 , and thereafter the calculation is repeated until provisional gains Gn are calculated based on the region setting result of blurred image Susn having a highest frequency band.
  • the frequency difference between blurred image Susi- 1 and blurred image Susi is small because their frequency bands are close to each other. Therefore, the blurred range, i.e., variation range of pixel levels in blurred image Susi- 1 becomes small at the boundary between the regions in which each pixel of image Susi is included, so that gains Gi for blurred image Susi may be calculated appropriately.
  • gain Gf according to a global level variation of image S 0 may be calculated without being influenced by the blurred range, i.e., variation range of pixel levels in blurred image Sus 0 at the boundary between the regions in which each pixel of image S 0 is included. Accordingly, high quality processed image S 2 without overshooting and undershooting may be obtained.
  • final gain Gf is calculated from a provisional gain calculated from blurred image Sus 0 based on the region setting result of image S 0 .
  • an arrangement maybe adopted in which an average value of each pixel of blurred image Sus 0 in each of the one or more regions in which each pixel of blurred image Sus 0 is included is calculated and a gain for each pixel is calculated based on the average value such that the lower the level of each pixel the greater the gain.
  • FIG. 17 shows the average luminance value calculation result of blurred image Sus 0 .
  • an average value of luminance values Y for the lower left region is also calculated in FIG. 17 .
  • the image processing apparatus of the present invention is applied to a digital camera, but the image processing apparatus may be used as a stand-alone apparatus.
  • the image processing apparatus is provided with an interface, such as a card reader, for receiving an image obtained by a digital camera or the like.
  • luminance value Y is calculated as the pixel level, but RGB average value of each pixel, only G value, or maximum value of RGB values may be used as the pixel level.
  • an average value of gains for pixels in each of one or more regions in which each pixel is included is calculated, but the weighted average according to the distance from each pixel, intermediate value, or the like may be used, instead of the average value.
  • a gain to be multiplied to each pixel of image S 0 is calculated, but a gain to be added to or subtracted from each pixel may be calculated.
  • gain processing unit 12 performs gain processing by adding the gain to or subtracting from each pixel of image S 0 .
  • gains for the entirety of image S 0 are calculated and dynamic rang compression is performed for the entirety of image S 0 , but an arrangement may be adopted in which gains only for a high luminance region or low luminance region are calculated and the dynamic range of only the high luminance region or low luminance region is compressed.
  • the final gain is calculated from provisional gain G 0 with respect to blurred image Sus 0 having a lowest frequency band, but the frequency band for calculating the provisional gain is not limited to the lowest frequency band and another frequency band other than a predetermined highest frequency band may be used. Still further, it is not necessary to calculate the final gain using region setting results up to blurred image Susn of a highest frequency band, and the final gain may be calculated using region setting results up to blurred image of a predetermined frequency band.
  • apparatus 1 according to the embodiments of the present invention has been described, but a program for causing a computer to function as means corresponding to level information calculation unit 31 , low frequency image generation unit 32 , region setting unit 33 , gain calculation unit 34 , and multiplication unit 35 , and to perform processing like that shown in FIGS. 14 , and 16 is another embodiment of the present invention. Further, a computer readable recording medium on which is recorded such a program is still another embodiment of the present invention.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Image Processing (AREA)
  • Facsimile Image Signal Circuits (AREA)
  • Studio Devices (AREA)
US12/434,871 2008-05-09 2009-05-04 Image processing apparatus, method, and program Abandoned US20090278957A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US13/471,016 US8345121B2 (en) 2008-05-09 2012-05-14 Image processing apparatus, method, and program

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2008123046A JP4944061B2 (ja) 2008-05-09 2008-05-09 画像処理装置および方法並びにプログラム
JP2008-123046 2008-05-09

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US13/471,016 Division US8345121B2 (en) 2008-05-09 2012-05-14 Image processing apparatus, method, and program

Publications (1)

Publication Number Publication Date
US20090278957A1 true US20090278957A1 (en) 2009-11-12

Family

ID=41060160

Family Applications (2)

Application Number Title Priority Date Filing Date
US12/434,871 Abandoned US20090278957A1 (en) 2008-05-09 2009-05-04 Image processing apparatus, method, and program
US13/471,016 Expired - Fee Related US8345121B2 (en) 2008-05-09 2012-05-14 Image processing apparatus, method, and program

Family Applications After (1)

Application Number Title Priority Date Filing Date
US13/471,016 Expired - Fee Related US8345121B2 (en) 2008-05-09 2012-05-14 Image processing apparatus, method, and program

Country Status (5)

Country Link
US (2) US20090278957A1 (ja)
EP (1) EP2116972A3 (ja)
JP (1) JP4944061B2 (ja)
KR (1) KR101650050B1 (ja)
CN (1) CN101577796B (ja)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100245615A1 (en) * 2008-01-08 2010-09-30 Fujitsu Limited Image processing apparatus and image processing method
US20140226902A1 (en) * 2013-02-13 2014-08-14 Canon Kabushiki Kaisha Image processing apparatus and image processing method
US9313375B1 (en) * 2014-06-03 2016-04-12 Amazon Technologies, Inc. Software-implemented graduated neutral density filter for balancing exposure of a photograph
US11887286B2 (en) 2018-11-02 2024-01-30 Sony Semiconductor Solutions Corporation Image processing device and image processing method to generate image for object recognition

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8457418B2 (en) * 2011-08-02 2013-06-04 Raytheon Company Local area contrast enhancement
JP6817779B2 (ja) 2016-10-20 2021-01-20 キヤノン株式会社 画像処理装置、その制御方法、プログラムならびに記録媒体

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060158529A1 (en) * 2004-12-27 2006-07-20 Konica Minolta Holdings, Inc. Image sensing apparatus and image processing method for use therein
US20080252791A1 (en) * 2007-04-13 2008-10-16 Tomoo Mitsunaga Image processing device and method, and program
US7587089B2 (en) * 2005-03-15 2009-09-08 Sunplus Technology Co., Ltd. Method and apparatus for image processing
US20100026857A1 (en) * 2008-07-29 2010-02-04 Samsung Digital Imaging Co., Ltd. Imaging device, method for controlling the imaging device, and recording medium recording the method
US7978927B2 (en) * 2007-03-07 2011-07-12 Marketech International Corp. Image processing apparatus

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2509503B2 (ja) 1992-09-11 1996-06-19 コニカ株式会社 画像処理方法及び装置
JP3738788B2 (ja) 1995-09-29 2006-01-25 富士写真フイルム株式会社 画像のダイナミックレンジ圧縮処理方法および装置
US6285798B1 (en) * 1998-07-06 2001-09-04 Eastman Kodak Company Automatic tone adjustment by contrast gain-control on edges
JP3208762B2 (ja) * 1998-11-18 2001-09-17 ソニー株式会社 画像処理装置及び画像処理方法
JP4556276B2 (ja) 2000-03-23 2010-10-06 ソニー株式会社 画像処理回路及び画像処理方法
US7791656B2 (en) * 2005-08-16 2010-09-07 Konica Minolta Holdings, Inc. Image sensing apparatus and image processing method
JP2007074373A (ja) * 2005-09-07 2007-03-22 Fujifilm Corp 画像処理装置、および画像処理方法
JP2007096509A (ja) * 2005-09-27 2007-04-12 Fujifilm Corp 画像処理装置、および画像処理方法
US7558436B2 (en) * 2006-07-20 2009-07-07 Max-Viz, Inc. Image dynamic range control for visual display

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060158529A1 (en) * 2004-12-27 2006-07-20 Konica Minolta Holdings, Inc. Image sensing apparatus and image processing method for use therein
US7525579B2 (en) * 2004-12-27 2009-04-28 Konica Minolta Holdings, Inc. Image sensing apparatus and image processing method for use therein
US7587089B2 (en) * 2005-03-15 2009-09-08 Sunplus Technology Co., Ltd. Method and apparatus for image processing
US7978927B2 (en) * 2007-03-07 2011-07-12 Marketech International Corp. Image processing apparatus
US20080252791A1 (en) * 2007-04-13 2008-10-16 Tomoo Mitsunaga Image processing device and method, and program
US20100026857A1 (en) * 2008-07-29 2010-02-04 Samsung Digital Imaging Co., Ltd. Imaging device, method for controlling the imaging device, and recording medium recording the method

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100245615A1 (en) * 2008-01-08 2010-09-30 Fujitsu Limited Image processing apparatus and image processing method
US8253820B2 (en) * 2008-01-08 2012-08-28 Fujitsu Limited Image processing apparatus and image processing method
US20140226902A1 (en) * 2013-02-13 2014-08-14 Canon Kabushiki Kaisha Image processing apparatus and image processing method
US9240037B2 (en) * 2013-02-13 2016-01-19 Canon Kabushiki Kaisha Image processing apparatus and image processing method
US9692985B2 (en) * 2013-02-13 2017-06-27 Canon Kabushiki Kaisha Image processing apparatus and image processing method for tone control by applying different gain
US9313375B1 (en) * 2014-06-03 2016-04-12 Amazon Technologies, Inc. Software-implemented graduated neutral density filter for balancing exposure of a photograph
US11887286B2 (en) 2018-11-02 2024-01-30 Sony Semiconductor Solutions Corporation Image processing device and image processing method to generate image for object recognition

Also Published As

Publication number Publication date
EP2116972A3 (en) 2012-09-26
JP2009272983A (ja) 2009-11-19
US20120224079A1 (en) 2012-09-06
US8345121B2 (en) 2013-01-01
CN101577796A (zh) 2009-11-11
JP4944061B2 (ja) 2012-05-30
KR101650050B1 (ko) 2016-08-22
KR20090117617A (ko) 2009-11-12
EP2116972A2 (en) 2009-11-11
CN101577796B (zh) 2013-10-09

Similar Documents

Publication Publication Date Title
US9025049B2 (en) Image processing method, image processing apparatus, computer readable medium, and imaging apparatus
US7548689B2 (en) Image processing method
KR101692401B1 (ko) 영상 처리 방법 및 장치
KR101643613B1 (ko) 디지털 영상 처리 장치, 영상 처리 방법 및 이를 기록한 기록 매체
KR101099401B1 (ko) 화상 처리 장치 및 컴퓨터가 판독 가능한 기록 매체
US8982232B2 (en) Image processing apparatus and image processing method
JP6116272B2 (ja) 画像処理装置及び画像処理方法、プログラム、記憶媒体
US8345121B2 (en) Image processing apparatus, method, and program
US20220124237A1 (en) Apparatus for generating high-dynamic-range image, method, and storage medium
JP4433883B2 (ja) ホワイトバランス補正装置及びホワイトバランス補正方法、プログラム、電子カメラ装置
JP4217041B2 (ja) フィルタ処理
JP7297406B2 (ja) 制御装置、撮像装置、制御方法およびプログラム
US9294685B2 (en) Image processing apparatus, electronic camera, and medium storing image processing program
JP2007329619A (ja) 映像信号処理装置と映像信号処理方法、および映像信号処理プログラム。
JP5589660B2 (ja) 画像処理装置、撮像装置及び画像処理プログラム
JP2009200743A (ja) 画像処理装置および画像処理方法および画像処理プログラムおよび撮像装置
US8102446B2 (en) Image capturing system and image processing method for applying grayscale conversion to a video signal, and computer-readable recording medium having recorded thereon an image processing program for applying grayscale conversion to a video signal
JP6786273B2 (ja) 画像処理装置、画像処理方法、及びプログラム
US8498494B2 (en) Method and apparatus for processing a digital image signal, and a recording medium having recorded thereon a program for executing the method
JP2008219230A (ja) 撮像装置及び画像処理方法
JP2009258284A (ja) 画像処理装置、撮像装置、画像処理方法およびプログラム
JP2020149589A (ja) 画像処理装置、撮像装置、画像処理方法、及びプログラム
US20240048822A1 (en) Image capture apparatus and control method for same
US8106977B2 (en) Image capturing system and image processing method for applying grayscale conversion to a video signal, and computer-readable recording medium having recorded thereon an image processing program for applying grayscale conversion to a video signal
JP2012133492A (ja) 画像処理装置およびプログラム

Legal Events

Date Code Title Description
AS Assignment

Owner name: FUJIFILM CORPORATION, JAPAN

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:TANAKA, SEIJI;REEL/FRAME:022632/0722

Effective date: 20090331

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION