Image Restoration

Version 1.0.0 (85.1 KB) by RFM
Performing Image Restoration - From the Degraded Image with MOTION BLUR and Random Noise.
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Updated 11 Jan 2020

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Basic Concept (SUMMARY)
1. Read an Input Image
2. Defining a Blurr Filter
3. Degrade the Image Quality by applying any filtering (eg Gaussian Blur, Motion Blur)
4. Addition of Minimal Random Noise to the degraded Image (using randn)
5. Computing DFT of Degraded Image
Steps (fft2, fftshift, log of absolute value for display)
6. Computing DFT of Filter (size equal to the image)
Steps (increase the size of filter, ifftshift, fft2, fftshift, log of absolute value for display)
7. Applying the REQUISITE METHOD FOR IMAGE RESTORATION
8. Display the Restored Image in Spatial Domain

Cite As

RFM (2024). Image Restoration (https://www.mathworks.com/matlabcentral/fileexchange/73891-image-restoration), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0