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%载入图像 RGB = imread('saturn.png'); %RGB转换为灰度图 I = rgb2gray(RGB); %加入高斯白噪声 J = imnoise(I,'gaussian',0,0.005); %采用自适应滤波 K = wiener2(J,[5 5]); %显示原始图像、加入噪声的图像以及滤波后的噪声 imshow(I) figure,imshow(J)

RGB = imread('saturn.png'); I = rgb2gray(RGB); h = [1 2 1; 0 0 0; -1 -2 -1]; I2 = filter2(h,I); imshow(I2,[]), colorbar

%载入图像 load trees %RGB转换为灰度图 I = ind2gray(X,map); imshow(I) %指定特定区域，并进行填充 I2 = roifill; imshow(I2)

%载入图像 RGB = imread('autumn.tif'); figure(1); imshow(RGB); %将真彩图转换为灰度图 I = rgb2gray(RGB); figure(2); imshow(I); %进行余弦变换 J = dct2(I); figure(3); imshow(log(abs(J)),[]); colormap(jet(64)); c

%例程7－1 噪声图像维纳滤波 % e.g.7-1.m for example7-1; %test the function of weina filter. RGB = imread('saturn.png'); I = rgb2gray(RGB); J = imnoise(I,'gaussian',0,0.005); figure, imshow(J); K = wien

function BasedLineINDrictC100() %校正c100图像（358，235，500）x0,y0,R % rgb=imread('D:\0.bmp'); rgb = imread('D:\dzf\fisheye image\C100\testImage0337.bmp'); [ height, width, v ] = size(rgb); [X0,Y0,R]

function [X0,Y0,R]=Yuan(rgb) %定义函数，获得圆形区域的圆心坐标及半径 r=rgb(:,:,1); g=rgb(:,:,2); b=rgb(:,:,3); I=0.59*r+0.11*g+0.3*b; %像素亮度计算公式 I=uint8(I); [Height,Width]=size(I); Thre=46; %预设阈值 for Row1=1:(

//------------------------------------------------------------------------------ // // HSL - RGB colour model conversions // // These four functions can be used to convert between the RGB and HSL

function hsl=rgb2hsl(rgb) %Converts Red-Green-Blue Color value to Hue-Saturation-Luminance Color value % %Usage % HSL = rgb2hsl(RGB) % % converts RGB, a M X 3 color matrix with values

function rgb=hsl2rgb(hsl) %Converts Hue-Saturation-Luminance Color value to Red-Green-Blue Color value % %Usage % RGB = hsl2rgb(HSL) % % converts HSL, a M X 3 color matrix with values