Covid-19 Images and Video Denoising Algorithms Based on Convolutional Neural Network CNNs
| Autor: | Salsabil Saad Saoud, Amira Lamreche, Zoubeida Messali |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Carry (arithmetic) Deep learning Noise reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION General Medicine Convolutional neural network Field (computer science) symbols.namesake Gaussian noise symbols Preprocessor Video denoising Artificial intelligence business Algorithm |
| Zdroj: | Algerian Journal of Signals and Systems. 6:122-129 |
| ISSN: | 2676-1548 2543-3792 |
| Popis: | In this paper, the most sophisticated denoising algorithms of images and video are applied and implemented. More precisely, we study and implement the video denoising algorithms "VBM3D", "VBM4D", "DVDNet" and "FastDVDnet". Much attention is given to the latest DVDNet and FastDVDNet algorithms, which are based on CNN. We carry out a detailed quantitative and qualitative comparative study between the considered algorithms. Two assessments are adapted; the first is a qualitative comparison based on the qualityof the images / videos and the second is quantitative in terms of PSNR and running time criteria. To see the direct impact of our study on the current pandemic, and to show the importance of image and video preprocessing algorithms in the field of medical imaging; we apply the considered denoising algorithms based on CNN on our built COVID- 19 dataset and TEST_PCR videos. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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