wiener2.zip_adjectivem88_wiener2_插值

function [f,noise] = wiener2(varargin)%WIENER2 Perform 2-D adaptive noise-removal filtering. % WIENER2 lowpass filters an intensity image that has been % degraded by constant power additive noise. WIENER2 uses a % pixel-wise adaptive Wiener method based on statistics % estimated from a local neighborhood of each pixel. % % J = WIENER2(I,[M N],NOISE) filters the image I using % pixel-wise adaptive Wiener filtering, using neighborhoods of % size M-by-N to estimate the local image mean and standard % deviation. If you omit the [M N] argument, M and N default to % 3. The additive noise (Gaussian white noise) power is assumed % to be NOISE. % % [J,NOISE] = WIENER2(I,[M N]) also estimates the additive % noise power before doing the filtering. WIENER2 returns this % estimate as NOISE. % % Class Support % ------------- % The input image I can be of class uint8, uint16, or double. % The output image J is of the same class as I. % % Example % ------- % I = imread('saturn.tif'); % J = imnoise(I,'gaussian',0,0.005); % K = wiener2(J,[5 5]); % imshow(J), figure, imshow(K) % % See also FILTER2, MEDFILT2.% The following syntax is grandfathered: % % J = WIENER2(I,[M N],[MBLOCK NBLOCK],NOISE) or [J,NOISE] = % WIENER2(I,[M N],[MBLOCK NBLOCK]) processes the intensity % image I as above but in blocks of size MBLOCK-by-NBLOCK. Use % J = WIENER2(I,[M N],SIZE(I),NOISE) to process the matrix all % at once. % Copyright 1993-2002 The MathWorks, Inc. % $Revision: 5.18 $ $Date: 2002/03/15 15:29:28 $ % Uses algorithm developed by Lee (1980). % Reference: "Two-Dimensional Signal and Image Processing" by % Jae S. Lim, pp.536-540. [g, nhood, ~, noise, msg] = ParseInputs(varargin{:});% 调用 ParseInput()处理不同的输入参数的情况 ,且将输入参数以数组的形式表示 if (~isempty(msg)) error(msg); end classin = class(g); classChanged = 0; if ~isa(g, 'double') classChanged = 1; g = im2double(g); end % Estimate the local mean of f. localMean = filter2(ones(nhood), g) / prod(nhood); %用一个所有的值全相等的小矩阵中的二维 FIR 滤波器对二维数据 g 进行滤波%其实质是利用小矩阵对 g 进行二维卷积运算，最终结果的维数大小 %等于 g 的维数，取的是卷积结果的中心部分。类似于求均值 % Estimate of the local variance of f. localVar = filter2(ones(nhood), g.^2) / prod(nhood) - localMean.^2; % 求 取 类 似 于 方 差 的 localVar 。 这 样 的 算 法 正 好 体 现 了 图 像 矩 阵中 %元素间的相关性 % Estimate the noise power if necessary. if (isempty(noise)) noise = mean2(localVar); %若没有输入 noise，则取 localVar 的均值作为 noise end % Compute result % f = localMean + (max(0, localVar - noise) ./ ... % max(localVar, noise)) .* (g - localMean); % % Computation is split up to minimize use of memory % for temp arrays. f = g - localMean; %去除图像信号中的直流分量，使得图像信号成为零均值的信号 g = localVar - noise; g = max(g, 0); localVar = max(localVar, noise); f = f ./ localVar; f = f .* g; f = f + localMean; %对处理后的信号再重新加上直流分量 if classChanged, f = changeclass(classin, f); %使图像矩阵的数据类型与输入时相同 end %%% %%% Subfunction ParseInputs %%% % function [g, nhood, block, noise, msg] = ParseInputs(varargin) % g = []; % nhood = [3 3]; % block = []; % noise = []; % msg = ''; % switch nargin% 表示输入参数个数的系统参数 % case 0 % msg = 'Too few input arguments.'; % return; % case 1 % % wiener2(I) % g = varargin{1};% 把输入的第一个参数赋值给 g % case 2 % g = varargin{1}; % switch prod(size(varargin{2})) % case 1 % % wiener2(I,noise) % noise = varargin{2}; % case 2 % % wiener2(I,[m n]) % nhood = varargin{2}; % otherwise % msg = 'Invalid input syntax'; % return; % end % case 3 % g = varargin{1}; % if (prod(size(varargin{3})) == 2) % % wiener2(I,[m n],[mblock nblock]) OBSOLETE % warning(['WIENER2(I,[m n],[mblock nblock]) is an obsolete syntax.',... % 'Omit the block size, the image matrix is processed all at once.']); % nhood = varargin{2}; % block = varargin{3}; % else % % wiener2(I,[m n],noise) % nhood = varargin{2}; % noise = varargin{3}; % end % case 4 % % wiener2(I,[m n],[mblock nblock],noise) OBSOLETE % warning(['WIENER2(I,[m n],[mblock nblock],noise) is an obsolete syntax.',... % 'Omit the block size, the image matrix is processed all at once.']); % g = varargin{1}; % nhood = varargin{2}; % block = varargin{3}; % noise = varargin{4}; % otherwise % msg = 'Too many input arguments.'; % return; % end % % checking if input image is a truecolor image-not supported by WIENER2 % if (ndims(g) == 3)% 判断是否为三维图像 % msg = 'WIENER2 does not support 3D truecolor images as an input.'; % return; % end; % if (isempty(block)) % block = bestblk(size(g)); % end