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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Histogram matching ： ウィキペディア英語版 Histogram matching In image processing, histogram matching or histogram specification is the transformation of an image so that its histogram matches a specified histogram. The well-known histogram equalization method is a special case in which the specified histogram is uniformly distributed. It is possible to use histogram matching to balance detector responses as a relative detector calibration technique. It can be used to normalize two images, when the images were acquired at the same local illumination (such as shadows) over the same location, but by different sensors, atmospheric conditions or global illumination. ==Algorithm== Given two images, the reference and the adjusted images, we compute their histograms. Following, we calculate the cumulative distribution functions of the two images' histograms – $F\_1()\backslash ,$ for the reference image and $F\_2()\backslash ,$ for the target image. Then for each gray level $G\_1\backslash in()$, we find the gray level $G\_2\backslash ,$ for which $F\_1(G\_1)=F\_2(G\_2)\backslash ,$, and this is the result of histogram matching function: $M(G\_1)=G\_2\backslash ,$. Finally, we apply the function $M()$ on each pixel of the reference image. 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「Histogram matching」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.