Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction
作者： Mila Nikolova , Michael K Ng , Chi-Pan Tam
关键词: Mathematics 、 Mathematical optimization 、 Image processing 、 Minification 、 Convex regularization 、 Fast Fourier transform 、 Predictor–corrector method 、 Iterative reconstruction 、 Image restoration 、 Regularization (mathematics)
摘要: Nonconvex nonsmooth regularization has advantages over convex for restoring images with neat edges. However, its practical interest used to be limited by the difficulty of computational stage which requires a nonconvex minimization. In this paper, we deal minimization methods image restoration and reconstruction. Our theoretical results show that solution problem is composed constant regions surrounded closed contours The main goal paper develop fast algorithms solve problem. experimental effectiveness efficiency proposed algorithms.
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