Name
Abstract | ||
|---|---|---|
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 image's sparse representations in over-complete dictionary, it reconstructs a simple threshold to realize image denoising. Experimental results demonstrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSO.2009.357 | CSO (1) |
Keywords | Field | DocType |
sparse representations,novel dictionary design algorithm,k-means clustering process,dictionary design algorithm,sparse decomposition algorithm,new denoising method,new signal representation theory,image denoising,over-complete dictionary,sparse representation,dictionaries,k means clustering,clustering algorithms,design optimization,least mean square,noise reduction,information science,image segmentation,underwater acoustics,algorithm design and analysis,marine technology,image reconstruction | Noise reduction,K-SVD,Computer science,Image segmentation,Artificial intelligence,Cluster analysis,Iterative reconstruction,Least mean squares filter,Algorithm design,Pattern recognition,Sparse approximation,Algorithm,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.41 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yinghao Liao | 1 | 201 | 6.56 |
| Quan Xiao | 2 | 1 | 0.75 |
| Xinghao Ding | 3 | 591 | 52.95 |
| Donghui Guo | 4 | 107 | 21.93 |