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Received:November 18, 2000 Revised:March 19, 2001
Received:November 18, 2000 Revised:March 19, 2001
Abstract:In order to restore degenerative images, which are go short of priori knowledge about original images, and explore new ways of x-ray tomographic image reconstruction, the experience of Spall and Cristion抯 simultaneous perturbation stochastic approximation (SPSA) method is drawn on, and this algorithm is extended to the high order and multivariate case, then a new gradient approximation algorithm with stochastic perturbation is presented. This algorithm does not need either a priori knowledge or a posteriori probability, and has convergence with excellent stability. Comparative experiments show that this algorithm converges to visually good images with excellent stability for restoration and reconstruction of images.
keywords: image reconstruction x-ray tomography L-mixing processe image restoration stochastic perturbation gradient
Foundation items:
Author Name | Affiliation |
LIU Chuan-cai | 福州大学,计算机科学与技术系,福建,福州,350002 |
FU Qing-xiang | 福州大学,计算机科学与技术系,福建,福州,350002 |
Reference text:
LIU Chuan-cai,FU Qing-xiang.An Image Restoration and Reconstruction Algorithm Based on Stochastic Perturbati on Gradient Approximation.Journal of Software,2002,13(10):2044-2050
LIU Chuan-cai,FU Qing-xiang.An Image Restoration and Reconstruction Algorithm Based on Stochastic Perturbati on Gradient Approximation.Journal of Software,2002,13(10):2044-2050