Question

我有这个代码将对图像执行高斯滤波（低通滤波器）。但是，此滤镜仅适用于灰度图像。如何改进它以便它可以在彩色图像上工作？我知道有许多内置函数，但我是图像处理的新手，我正在尝试学习基础知识。

%Read an Image
Img = imread('peppers.png');
Im = rgb2gray(Img);
I = double(Im);

%Design the Gaussian Kernel
%Standard Deviation
sigma = 1.76;

%Window size
sz = 4;
[x,y]=meshgrid(-sz:sz,-sz:sz);

M = size(x,1)-1;
N = size(y,1)-1;
Exp_comp = -(x.^2+y.^2)/(2*sigma*sigma);
Kernel= exp(Exp_comp)/(2*pi*sigma*sigma);

%Initialize
Output=zeros(size(I));
%Pad the vector with zeros
I = padarray(I,[sz sz]);

%Convolution
for i = 1:size(I,1)-M
    for j =1:size(I,2)-N
        Temp = I(i:i+M,j:j+M).*Kernel;
        Output(i,j)=sum(Temp(:));
    end
end
%Image without Noise after Gaussian blur
Output = uint8(Output);
figure,imshow(Output);

Answer 1

RGB图像由红色，绿色，蓝色通道组成。在RGB图像上执行图像处理

您必须将图像的三个组成部分分开
处理每个组件（R，G，B）一次

从修改过的R，G，B重构图像

img = imread('peppers.png');
R = img(:,:,1); %get the Red part
G = img(:,:,2); %get the Blue part
B = img(:,:,3); %get the Green part
R_gaussian = gaussianFilter(R); %write your own function name
G_gaussian = gaussianFilter(G); %or repeat the code by REPLACING I as 
B_gaussian = gaussianFilter(B); %Red Green Blue components
RGB_gaussian = cat(3,R_gaussian, G_gaussian, B_gaussian); %merging the components
%since you are learning you can do this for better unedrstanding
RGB_gaussian = zeros(size(img)); %make a matrix of size  of original image
RGB_gaussian(:,:,1)=R_gaussian; % Replace the values  
RGB_gaussian(:,:,2)=G_gaussian;
RGB_gaussian(:,:,3)=B_gaussian;

有关详细信息，这可能会有所帮助：http://www.bogotobogo.com/Matlab/Matlab_Tutorial_Digital_Image_Processing_6_Filter_Smoothing_Low_Pass_fspecial_filter2.php

用于RGB图像的Matlab低通滤波器

1 个答案: