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用于图象复原的离散L-曲线自适应算法
引用本文:霍智勇,;朱秀昌. 用于图象复原的离散L-曲线自适应算法[J]. 南京邮电学院学报(自然科学版), 2008, 0(4): 27-33
作者姓名:霍智勇,  朱秀昌
作者单位:[1]南京邮电大学传媒技术学院,江苏南京210003; [2]南京邮电大学通信与信息工程学院,江苏南京210003
摘    要:描述了一种自适应的离散L-曲线正则参数的计算方法,正则化方法为截断奇异值分解法。该算法不需要预置参数,能够滤除L-曲线上的局部特征,略掉局部拐点,确保了解的收敛。在不同的噪声背景下以及不同尺度下我们进行了数值测试,并将测试结果与最优正则解进行对比分析。实验表明,该算法对图像的复原效果、可靠性和稳定性要优于传统的算法。

关 键 词:图像复原  截断奇异值分解  正则化  L-曲线  参数选择方法

An Adaptive Discrete L-Curve Algorithm for Image Restoration
Affiliation:HUO Zhi-yong, ZHU Xiu-chang (1. College of Communication Technology,Nanjing University of Postsand Telecommunicatlons,Nanjing 210003,China ;2. College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003 ,China)
Abstract:This paper describes an adaptive Discrete L-curve algorithm to calculate regular parameters. The regularization method based on truncated singular value decomposition without pre-defined parameters. It can filter small local phenomena and local corners to guarantee the convergence of the solution. Numerical examples have been made in different noise level and scales to compare the testing results with the optimal regular solution. The experiments have shown that the proposed algorithm is superior to traditional algorithm ones in terms of image restoration, effect, robustness and stability.
Keywords:Image restoration  TSVD  Reaularization  L-Curve  Parameter-choice method
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