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Sparse representation for color image restoration.

Publication ,  Journal Article
Mairal, J; Elad, M; Sapiro, G
Published in: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
January 2008

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 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. 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.

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Published In

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

DOI

EISSN

1941-0042

ISSN

1057-7149

Publication Date

January 2008

Volume

17

Issue

1

Start / End Page

53 / 69

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Colorimetry
  • Color
  • Artificial Intelligence & Image Processing
  • Artificial Intelligence
  • Algorithms
 

Citation

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Mairal, J., Elad, M., & Sapiro, G. (2008). Sparse representation for color image restoration. IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, 17(1), 53–69. https://doi.org/10.1109/tip.2007.911828
Mairal, Julien, Michael Elad, and Guillermo Sapiro. “Sparse representation for color image restoration.IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society 17, no. 1 (January 2008): 53–69. https://doi.org/10.1109/tip.2007.911828.
Mairal J, Elad M, Sapiro G. Sparse representation for color image restoration. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 2008 Jan;17(1):53–69.
Mairal, Julien, et al. “Sparse representation for color image restoration.IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, vol. 17, no. 1, Jan. 2008, pp. 53–69. Epmc, doi:10.1109/tip.2007.911828.
Mairal J, Elad M, Sapiro G. Sparse representation for color image restoration. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 2008 Jan;17(1):53–69.

Published In

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society

DOI

EISSN

1941-0042

ISSN

1057-7149

Publication Date

January 2008

Volume

17

Issue

1

Start / End Page

53 / 69

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Colorimetry
  • Color
  • Artificial Intelligence & Image Processing
  • Artificial Intelligence
  • Algorithms