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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 Generalized signal averaging ： ウィキペディア英語版 Generalized signal averaging In many cases only one image with noise is available, and averaging is then realized in a local neighbourhood. Results are acceptable if the noise is smaller in size than the smallest objects of interest in the image, but blurring of edges is a serious disadvantage. In the case of smoothing within a single image, one has to assume that there are no changes in the gray levels of the underlying image data. This assumption is clearly violated at locations of image edges, and edge blurring is a direct consequence of violating the assumption. Averaging is a special case of discrete convolution. For a 3 by 3 neighbourhood, the convolution mask ''M'' is: $$ M = \frac \begin1 & 1 & 1 \\ 1 & 1 & 1 \\ 1 & 1 & 1 \\ \end The significance of the central pixel may be increased, as it approximates the properties of noise with a Gaussian probability distribution: $$ M = \frac \begin1 & 1 & 1 \\ 1 & 2 & 1 \\ 1 & 1 & 1 \\ \end $$ M = \frac \begin1 & 2 & 1 \\ 2 & 4 & 2 \\ 1 & 2 & 1 \\ \end A suitable page for beginners about matrices is at: http://www.gamedev.net/reference/programming/features/imageproc/page2.asp The whole article starts on page: http://www.gamedev.net/reference/programming/features/imageproc/ 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「Generalized signal averaging」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.