Image processing apparatus, method, and program
a technology of image processing and apparatus, applied in the field of image processing methods, can solve the problems of image quality degradation, inability to completely eliminate overshooting or undershooting adjacent to an edge, etc., and achieve the effect of high quality
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first embodiment
[0063]Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. FIG. 1 is a schematic block diagram of a digital camera to which the image processing apparatus according to the present invention is applied, illustrating the configuration thereof. As illustrated in FIG. 1, 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.
[0064]FIG. 2 illustrates a configuration of imaging unit 2. As illustrated in FIG. 2, imaging unit 2 includes lens 20, aperture 21, shutter 22, CCD 23, analog front-end (AFE) 24, and A / D converter 25.
[0065]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...
second embodiment
[0108] a plurality of blurred images Sus0 to Susn of different frequency bands is generated from image S0, and according to the level of each pixel of each of blurred images Sus1 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 Sus1 to Susn in which each pixel is included. Then, from provisional gains G0 calculated based on blurred image Sus0 having a lowest frequency band, provisional gains G1 is calculated based on the region setting result of blurred image Sus1, 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.
[0109]Here, 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 b...
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