Inverse Techniques for Efficient Corneal Image Restoration
| Autor: | Huda Ibrahim Ashiba, Abd El-Rahman Farouk, El_Sayed M. El_Rabaie, M. I. Dessouky, F. E. Abd El-Samie, Adel S. El-Fishawy, Ghada M. El-Banby |
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| Rok vydání: | 2020 |
| Předmět: |
Minimum mean square error
genetic structures Mean squared error Correlation coefficient business.industry Computer science Process (computing) General Medicine Peak signal-to-noise ratio eye diseases Image (mathematics) Computer vision sense organs Artificial intelligence business Focus (optics) Image restoration |
| Zdroj: | Menoufia Journal of Electronic Engineering Research. 29:70-74 |
| ISSN: | 1687-1189 |
| DOI: | 10.21608/mjeer.2020.103954 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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