matlab图像处理----基于Prewitt算子的梯度图像，锐化图像及方向图像

>> clear all
>> 
>> Image = im2double(rgb2gray(imread('C001H001S0001000001.jpg')));
>> H1 = [-1 -1 -1;0 0 0;1 1 1];
>> H2 = [0 -1 -1;1 0 -1;1 1 0];
>> H3 = [1 0 -1;1 0 -1;1 0 -1];
>> H4 = [1 1 0;1 0 -1;0 -1 -1];
>> H5 = [1 1 1;0 0 0;-1 -1 -1];
>> H6 = [0 1 1;-1 0 1;-1 -1 0];
>> H7 = [-1 0 1;-1 0 1;-1 0 1];
>> H8 = [-1 -1 0;-1 0 1;0 1 1];
>> R1 = abs(imfilter(Image,H1));
>> R2 = abs(imfilter(Image,H2));
>> R3 = abs(imfilter(Image,H3));
>> R4 = abs(imfilter(Image,H4));
>> R5 = abs(imfilter(Image,H5));
>> R6 = abs(imfilter(Image,H6));
>> R7 = abs(imfilter(Image,H7));
>> R8 = abs(imfilter(Image,H8));   %8个模板与其对应的图像滤波
>> R = cat(3,R1,R2,R3,R4,R5,R6,R7,R8);
>> [gradI,thrtaI] = max(R,[],3);   %寻找最大响应作为梯度图像
>> sharpI = gradI + Image;         %锐化图像
>> thresh = mean(gradI(:)) +2*std(gradI(:)); %设定阈值
>> thrtaI(gradI<thresh) = 0; %保留梯度大于阈值的像素点
>> subplot(221),imshow(Image),title('原图');
>> subplot(222),imshow(gradI),title('梯度图像');
>> subplot(223),imshow(sharpI),title('锐化图像');
>> subplot(224),imshow(Image),title('方向图像');