Image Restoration

versión 1.0.0 (85.1 KB) por RFM
Performing Image Restoration - From the Degraded Image with MOTION BLUR and Random Noise.

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Actualizada 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

Citar como

RFM (2022). Image Restoration (https://www.mathworks.com/matlabcentral/fileexchange/73891-image-restoration), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2019b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux

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