A Novel Dictionary Design Algorithm for Sparse Representations

摘要：

Sparse representation based on over-complete dictionary is a new signal representation theory. Recent activity in this field concentrated mainly on the study of sparse decomposition algorithm and dictionary design algorithm. In this paper, a novel dictionary design algorithm called K-LMS is proposed. It generalized the K-Means clustering process, for adapting dictionaries to achieve sparse representation of signals. As regards to the image denoising, a new denoising method is introduced. With the application of images sparse representations in over-complete dictionary, it reconstructs a simple threshold to realize image denoising. Experimental results demonstrate the effectiveness of the proposed method.

作者: Yinghao Liao Quan Xiao Xinghao Ding Donghui Guo

作者单位: School of Information Science and Technology, Xiamen University, Xiamen, 361005, China School of Information Science and Technology, Key Laboratory of Underwater Acoustic Communication an

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 831-834

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）