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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 Non-local means ： ウィキペディア英語版 Non-local means Non-local means is an algorithm in image processing for image denoising. Unlike "local mean" filters, which take the mean value of a group of pixels surrounding a target pixel to smooth the image, non-local means filtering takes a mean of all pixels in the image, weighted by how similar these pixels are to the target pixel. This results in much greater post-filtering clarity, and less loss of detail in the image compared with local mean algorithms. If compared with other well-known denoising techniques, such as the Gaussian smoothing model, the anisotropic diffusion model, the total variation denoising, the neighborhood filters and an elegant variant, the Wiener local empirical filter, the translation invariant wavelet thresholding, the non-local means method noise looks more like white noise. Recently non-local means has been extended to other image processing applications such as deinterlacing and view interpolation. ==Definition== Suppose $\backslash Omega$ is the area of an image, and $p$ and $q$ are two points within the image. Then, the algorithm is: :$u(p)\; =\; \backslash int\_\backslash Omega\; v(q)\; f(p,q)dq.$ where $u(p)$ is the filtered value of the image at point $p$, $v(q)$ is the unfiltered value of the image at point $q$, $f(p,q)$ is the weighting function, and the integral is evaluated over $\backslash forall\; q\backslash in\backslash Omega$. $C(p)$ is a normalizing factor, given by: :$C(p)\; =\; \backslash int\_\backslash Omega\; f(p,q)dq.$ 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「Non-local means」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.