A Novel Dictionary Design Algorithm for Sparse Representations
| Autor: | Donghui Guo, Yinghao Liao, Xinghao Ding, Quan Xiao |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
K-SVD
business.industry Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Data_CODINGANDINFORMATIONTHEORY Sparse approximation Image segmentation Field (computer science) Image (mathematics) Computer Science::Computer Vision and Pattern Recognition Discrete cosine transform Algorithm design Artificial intelligence business Cluster analysis Algorithm |
| Zdroj: | CSO (1) |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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