Matlab image high pass filter

Matlab image high pass filter DEFAULT

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Image processing demo - high pass filter

version ( KB) by Bogumila & Zbigniew MROZEK

Graphic processing with MATLAB only (no toolboxes). High-pass filtering process example included.

Low-pass filtering is easy and always works fine (not included here). High-pass filtering needs conversion of numbers from integer to float before processing and then conversion back to integer -- to keep numbers within their limits. Lena.jpg example is included. Presented on EAEEIE conference ("Re-inventing Image Processing teaching") and published in a book MATLAB and Simulink by Bogumila & Zbigniew MROZEK,

Cite As

Bogumila & Zbigniew MROZEK (). Image processing demo - high pass filter (, MATLAB Central File Exchange. Retrieved .

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


close all;

imtool close all;



fontSize = 20;

folder = fullfile(matlabroot, '\toolbox\images\imdemos');

baseFileName = 'cameraman.tif';

fullFileName = fullfile(folder, baseFileName);

fullFileName = fullfile(folder, baseFileName);

if ~exist(fullFileName, 'file')

fullFileName = baseFileName;

if ~exist(fullFileName, 'file')

errorMessage = sprintf('Error: %s does not exist.', fullFileName);





grayImage = imread(fullFileName);

[rows columns numberOfColorBands] = size(grayImage);

subplot(2, 2, 1);

imshow(grayImage, []);

title('Original Grayscale Image', 'FontSize', fontSize);

set(gcf, 'Position', get(0,'Screensize'));

set(gcf,'name','Demo by ImageAnalyst','numbertitle','off')

kernel1 = -1 * ones(3)/9;

kernel1(2,2) = 8/9

filteredImage = imfilter(single(grayImage), kernel1);

subplot(2, 2, 2);

imshow(filteredImage, []);

title('Filtered Image', 'FontSize', fontSize);

kernel2 = [-1 -2 -1; -2 12 -2; -1 -2 -1]/16;

filteredImage = imfilter(single(grayImage), kernel2);

subplot(2, 2, 3);

imshow(filteredImage, []);

title('Filtered Image', 'FontSize', fontSize);

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MATLAB &#; Ideal Highpass Filter in Image Processing

In the field of Image Processing, Ideal Highpass Filter (IHPF) is used for image sharpening in the frequency domain. Image Sharpening is a technique to enhance the fine details and highlight the edges in a digital image. It removes low-frequency components from an image and preserves high-frequency components.

This ideal highpass filter is the reverse operation of the ideal lowpass filter. It can be determined using the following relation-  $H_{H P}(u, v)=1-H_{L P}(u, v)$
where, $H_{H P}(u, v)$ is the transfer function of the highpass filter and $H_{L P}(u, v)$ is the transfer function of the corresponding lowpass filter.

The transfer function of the IHPF can be specified by the function-
 $H(u, v)=\left\{\begin{array}{ll}0 & D(u, v) \leq D_{0} \\ 1 & D(u, v)>D_{0}\end{array}\right.$


Step 1: Input &#; Read an image
Step 2: Saving the size of the input image in pixels
Step 3: Get the Fourier Transform of the input_image
Step 4: Assign the Cut-off Frequency D_{0}
Step 5: Designing filter: Ideal High Pass Filter
Step 6: Convolution between the Fourier Transformed input image and the filtering mask
Step 7: Take Inverse Fourier Transform of the convoluted image
Step 8: Display the resultant image as output

Implementation in MATLAB:

Input Image &#;


My Personal Notesarrow_drop_up
Design a simple High Pass RC Filter using basic blocks of Simulink in MATLAB

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Pass high filter image matlab

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Low pass filters for images using Matlab

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