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A Review on Digital Image Restoration Process

by Sujita Pillai, Sanjay Khadagade
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 158 - Number 7
Year of Publication: 2017
Authors: Sujita Pillai, Sanjay Khadagade
10.5120/ijca2017912862

Sujita Pillai, Sanjay Khadagade . A Review on Digital Image Restoration Process. International Journal of Computer Applications. 158, 7 ( Jan 2017), 40-42. DOI=10.5120/ijca2017912862

@article{ 10.5120/ijca2017912862,
author = { Sujita Pillai, Sanjay Khadagade },
title = { A Review on Digital Image Restoration Process },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 158 },
number = { 7 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 40-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume158/number7/26924-2017912862/ },
doi = { 10.5120/ijca2017912862 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:04:15.189317+05:30
%A Sujita Pillai
%A Sanjay Khadagade
%T A Review on Digital Image Restoration Process
%J International Journal of Computer Applications
%@ 0975-8887
%V 158
%N 7
%P 40-42
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image restoration is the process of restoring degraded images which cannot be taken again or the process of obtaining the image again is costlier. We can restore the images by prior knowledge of the noise or the disturbance that causes the degradation in the image. Image restoration is done in two domains: spatial domain and frequency domain .image can provide an insight for filtering operations. After the filtering, the image is remapped into spatial domain by inverse Fourier transform to obtain the restored image. Restoration efficiency was checked by taking signal to noise ratio (snr) and mean square error(mse) into considerations..

References
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Index Terms

Computer Science
Information Sciences

Keywords

Restoration De-blur De-convolution Filtering Noise.

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