A low complexity but effective method in image and video detail enhancement - in-place similarity is proposed. In-place similarity is the statistic result of different kinds of nature image patches when similarity mea...
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A low complexity but effective method in image and video detail enhancement - in-place similarity is proposed. In-place similarity is the statistic result of different kinds of nature image patches when similarity measurement is done in super resolution research, finding that patches in the upscale image have a good match around its original location in the corresponding lower ones. On the basis of the in-place similarity, a simple assumption is made that detail layer is the high-frequency component of twice search and patch match result. Then, images under the framework of super resolution techniques are enhanced. Unlike many current algorithms that need to adjust parameters for different images to acquire best outputs the approach mentioned here is adaptive. Moreover, many algorithms have outcome with intensity and contrast change, the algorithm proposed here can prevent images from over enhancement with obvious nature looking effect. Extensive experiments demonstrate that the algorithm mentioned here is simple with robust good performance both subjectively and objectively. It is particularly useful for practical applications and easily hardware implemented in FPGA, where input images require diverse detail textures.
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