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103954

Inverse Techniques for Efficient Corneal Image Restoration

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Last updated: 25 Dec 2024

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Abstract

This paper presents two proposed approaches for digital restoration of corneal images. The first algorithm is based on Wiener Restoration approach. The second algorithm depends on regularized image restoration. As corneal images are usually acquired with confocal microscopes. Hence if the corneal layer is outside the focus of the microscopes, the image will be blurred. To solve this problem, the restoration process can be applied on the corneal image. Both Linear Minimum Mean Square Error (LMMSE) and regularized restoration are implemented. The evaluation metrics used to test the performance of the proposed restoration approaches are mean square error (MSE), peak signal to noise ratio (PSNR) and correlation coefficient. Simulations results reveal good success in restoration of corneal images refer to the mentioned evaluation metrics and appearance view.

DOI

10.21608/mjeer.2020.103954

Authors

First Name

Abd El-Rahman

Last Name

Farouk

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Affiliation

Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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First Name

H.I.

Last Name

Ashiba

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-

Affiliation

Department of Electronics and Electrical Communications, Bilbis higher institute of Engineering, Bilbis, sharqia , Egypt

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First Name

G.M.

Last Name

Elbanby

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-

Affiliation

Department of Automatic Control, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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First Name

A.S.

Last Name

El-Fishawy

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-

Affiliation

Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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First Name

M. I.

Last Name

Dessouky

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-

Affiliation

Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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First Name

E.M.

Last Name

El- Rabaie

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-

Affiliation

Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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First Name

F.E.

Last Name

Abd El-Samie

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-

Affiliation

Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

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Volume

29

Article Issue

2

Related Issue

15327

Issue Date

2020-07-01

Receive Date

2020-07-20

Publish Date

2020-07-01

Page Start

70

Page End

74

Print ISSN

1687-1189

Online ISSN

2682-3535

Article File

MJEER_Volume 29_Issue 2_Pages 70-74.pdf

PDF . 1.0MB

Link

https://mjeer.journals.ekb.eg/article_103954.html

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https://mjeer.journals.ekb.eg/service?article_code=103954

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Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Inverse Techniques for Efficient Corneal Image Restoration

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Article

Created At

22 Jan 2023