Inverse Techniques for Efficient Corneal Image Restoration | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 13, Volume 29, Issue 2, July 2020, Page 70-74 PDF (987.25 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2020.103954 | ||||
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| Authors | ||||
| Abd El-Rahman Farouk1; H.I. Ashiba2; G.M. Elbanby3; A.S. El-Fishawy1; M. I. Dessouky1; E.M. El- Rabaie1; F.E. Abd El-Samie1 | ||||
| 1Department of Electronics and Electrical Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt | ||||
| 2Department of Electronics and Electrical Communications, Bilbis higher institute of Engineering, Bilbis, sharqia , Egypt | ||||
| 3Department of Automatic Control, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt | ||||
| 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. | ||||
| References | ||||
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