Friday, 2 October 2020

MATLAB code of Image restoration using joint statistical modeling

Hello, friends today I am posting one project in the field of Digital image processing. The title of the project is Image restoration using joint statistical modeling in the space-transform domain. Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image. Corruption may come in many forms such as motion blurnoise, and camera misfocus. The objective of image restoration techniques is to reduce noise and recover resolution loss Image processing techniques are performed either in the image domain or the frequency domain. The matlab implementation of the image restoration is shown in the following YouTube video. Just have a look.

YouTube video of the MATLAB code of Image Restoration:

Image restoration is different from image enhancement in that the latter is designed to emphasize features of the image that make the image more pleasing to the observer, but not necessarily to produce realistic data from a scientific point of view.

The following steps are involved in the project:
-- Take noisy or corrupted image from the input database
-- Apply image restoration technique using joint statistical modeling.
-- Find initial PSNR of the deblurred image.
-- Now get the results for different iterations.
-- Gradually from 1 to n iteration PSNR will increases.
-- Finally, we will get a deblurred or denoised image.

MATLAB Implementation of the Image Restoration Project:

Blank MATLAB GUI of Image restoration project

MATLAB GUI of Image restoration project

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