1. Sparse Representation for Color Image Restoration.
- Author
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Mairal, Julien, Elad, Michael, and Sapiro, Guillermo
- Subjects
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ALGORITHMS , *IMAGE processing , *COMPUTER graphics , *IMAGING systems , *INFORMATION processing , *NOISE , *SOUND , *ALGEBRA , *SIGNALS & signaling - Abstract
Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. In particular, the design of well adapted dictionaries for images has been a major challenge. The K-SVD has been recently proposed for this task [1] and shown to perform very well for various grayscale image processing tasks. In this paper, we address the problem of learning dictionaries for color images and extend the K-SVD-based grayscale image denoising algorithm that appears in [21. This work puts forward ways for handling nonhomogeneous noise and missing information, paving the way to state-of-the-art results in applications such as color image denoising, demosaicing, and inpainting, as demonstrated in this paper. [ABSTRACT FROM AUTHOR]
- Published
- 2008
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