How do I use IMFILTER to high pass filter an image?

How can I high pass filter an image (A) using IMFILTER(A,H)? What must the filter matrix (H) be to perform a high pass filter?

Answer 1

[Ashish Uthama]

This tutorial might help.

[Image Analyst]

I've never seen a panda (the web site's example image) look like that. Looks more like a house cat to me.

[Walter Roberson]

One could hypothesize that it is a picture of a Red Panda, which is a small whiskered mammal about the size of a small dog. However, the ears are clearly not right for a red panda. Felis Catus, also known as Felis Domesticus, would seem to be a much better match.

[Ivan Spector]

Is the tutorial link above still live? I could not access it and had the same quesiton.

[Image Analyst]

It looks like the tutorial is no longer online. The link to the course is:

http://catalog.hmc.edu/preview_course_nopop.php?catoid=18&coid=6228

[DGM]

It's archived

https://web.archive.org/web/20210129170749/http://fourier.eng.hmc.edu/e161/lectures/gradient/node1.html

Answer 2

[Image Analyst]

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
fontSize = 20;

% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'cameraman.tif';
fullFileName = fullfile(folder, baseFileName);
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.
subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'Position', get(0,'Screensize')); 
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 

% Filter 1
kernel1 = -1 * ones(3)/9;
kernel1(2,2) = 8/9
% Filter the image.  Need to cast to single so it can be floating point
% which allows the image to have negative values.
filteredImage = imfilter(single(grayImage), kernel1);
% Display the image.
subplot(2, 2, 2);
imshow(filteredImage, []);
title('Filtered Image', 'FontSize', fontSize);

% Filter 2
kernel2 = [-1 -2 -1; -2 12 -2; -1 -2 -1]/16;
% Filter the image.  Need to cast to single so it can be floating point
% which allows the image to have negative values.
filteredImage = imfilter(single(grayImage), kernel2);
% Display the image.
subplot(2, 2, 3);
imshow(filteredImage, []);
title('Filtered Image', 'FontSize', fontSize);

[Ashish Uthama]

+1, tagging as a tutorial

[Image Analyst]

I've never heard of filter1. imfilter and filter2 should give the same answer.

Answer 3

[Tony]

A typical high-pass (or high emphasize filter) would be an unsharp mask.

H = fspecial('unsharp');

Answer 4

[Pramod Bhat]

Simple averaging your image can fulfill your need if u are not particular with the pass band.

[David Young]

That would be low-pass.