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PatchMatch
The core PatchMatch algorithm quickly finds correspondences between small square regions (or patches) of an image. The algorithm can be used in various applications such as object removal from images, reshuffling or moving contents of images, or retargeting or changing aspect ratios of images. ==Algorithm== The goal of the algorithm is to find the patch correspondence by defining a nearest-neighbor field (NNF) as a function of offsets, which is over all possible matches of patch (location of patch centers) in image A, for some distance function of two patches . So, for a given patch coordinate in image and its corresponding nearest neighbor in image , is simply . However, if we search for every point in image , the work will be too hard to complete. So the following algorithm is done in a randomized approach in order to accelerate the calculation speed. The algorithm has three main components. Initially, the nearest-neighbor field is filled with either random offsets or some prior information. Next, an iterative update process is applied to the NNF, in which good patch offsets are propagated to adjacent pixels, followed by random search in the neighborhood of the best offset found so far. Independent of these three components, the algorithm also use a coarse-to-fine approach by building an image pyramid to obtain the better result.
抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「PatchMatch」の詳細全文を読む
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