NON-CONVEX HYBRID TOTAL VARIATION FOR RESTORING MEDICAL IMAGE CORRUPTED BY POISSON NOISE
Copyright policy )NON-CONVEX HYBRID TOTAL VARIATION FOR RESTORING MEDICAL IMAGE CORRUPTED BY POISSON NOISE
Abstract. In this work, we proposed the hybrid non-convex regularizers for Poisson noise removal on medical images. The model is built by a combination of non-convex total variation and non-convex fractional total variation. The proposed model allows for avoiding the annoying staircase artifacts and obtaining the reconstruction results with sharp and neat edges during the noise removal process. For handling the minimization problem, we employ the alternating minimization method associated with the iteratively reweighted l1 algorithm. Numerical experiments illustrate the efficiency of the proposed model and corresponding algorithm.
- Tula State University Russian Federation
- Da Nang University of Economics Viet Nam
- University of Da Nang Viet Nam
- University of Science and Technology Yemen
Technology, Artificial intelligence, Biomedical Engineering, Geometry, Noise (video), FOS: Medical engineering, Astrophysics, Engineering, Multispectral and Hyperspectral Image Fusion, Media Technology, FOS: Mathematics, Image (mathematics), Applied optics. Photonics, Image Denoising, Image Fusion, Minification, T, Physics, Mathematical optimization, Statistics, Detector, Advances in Photoacoustic Imaging and Tomography, Engineering (General). Civil engineering (General), Computer science, Gaussian Noise, Convex combination, TA1501-1820, Convex optimization, Process (computing), Poisson Noise, Regular polygon, Algorithm, Operating system, Computer Science, Physical Sciences, Shot noise, Variation (astronomy), Poisson distribution, Telecommunications, Computer Vision and Pattern Recognition, TA1-2040, Image Denoising Techniques and Algorithms, Mathematics
Technology, Artificial intelligence, Biomedical Engineering, Geometry, Noise (video), FOS: Medical engineering, Astrophysics, Engineering, Multispectral and Hyperspectral Image Fusion, Media Technology, FOS: Mathematics, Image (mathematics), Applied optics. Photonics, Image Denoising, Image Fusion, Minification, T, Physics, Mathematical optimization, Statistics, Detector, Advances in Photoacoustic Imaging and Tomography, Engineering (General). Civil engineering (General), Computer science, Gaussian Noise, Convex combination, TA1501-1820, Convex optimization, Process (computing), Poisson Noise, Regular polygon, Algorithm, Operating system, Computer Science, Physical Sciences, Shot noise, Variation (astronomy), Poisson distribution, Telecommunications, Computer Vision and Pattern Recognition, TA1-2040, Image Denoising Techniques and Algorithms, Mathematics
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