A ’BGR’ image.

Now in terms of the filtering with a Gaussian, if you apply a 3x3 to every channel, that would be the same if you do in RGB or in BGR as you are averaging pixels in a channel.

Hope that answers your question.

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Ben Ma 2021-9-9

Can you also apply a 3x3 Gaussian filter to the original RGB image please? thanks

Constantino Carlos Reyes-Aldasoro 2021-9-9

在 MATLAB Online 中打开

Yes, you can apply the filter to the original or to the transformed. E.g. to apply to the RGB you do the following:

image1=imread('peppers.png');

image1_filtered = imfilter(image1, fspecial('Gaussian',3,1));

figure

subplot(221)

imagesc(image1)

subplot(222)

imagesc(image1_filtered)

subplot(223)

imagesc(image1(100:150,100:150,:))

subplot(224)

imagesc(image1_filtered(100:150,100:150,:))

If you want to apply to the transformed, do the same once it has been transformed.

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Answer 2

Image Analyst 2021-9-9

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1449269-a-bgr-image#answer_784319

在 MATLAB Online 中打开

Ben, you can use imgaussfilt(). It's very straightforward but let us know if you can't figure out my code below.

clc;    % Clear the command window.
clear all;
close all;
workspace;  % Make sure the workspace panel is showing.
format short g;
format compact;
fontSize = 15;
fprintf('Beginning to run %s.m ...\n', mfilename);
rgbImage = imread('peppers.png');
subplot(2, 1, 1);
imshow(rgbImage);
title('Original Image', 'FontSize', fontSize);
% Split into channels.
[r, g, b] = imsplit(rgbImage);
% Blur each channel.
sigma = 9; % Whatever.
smoothr = imgaussfilt(r, sigma);
smoothg = imgaussfilt(g, sigma);
smoothb = imgaussfilt(b, sigma);
% Combine individual blurred color channels into a new RGB image.
blurredImage = cat(3, smoothr, smoothg, smoothb);
% Display the blurred image.
subplot(2, 1, 2);
imshow(blurredImage);
caption = sprintf('Blurred with a sigma of %.1f', sigma);
title(caption, 'FontSize', fontSize);