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Impulsive noise removal from images using sparse representation and optimization methods

Beygi Harchegani, S ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/ISSPA.2010.5605449
  3. Publisher: 2010
  4. Abstract:
  5. In this paper, we propose a new method for impulsive noise removal from images. It uses the sparsity of natural images when they are expanded by mean of a good learned dictionary. The zeros in sparse domain give us an idea to reconstruct the pixels that are corrupted by random-value impulse noises. This idea comes from this reality that noisy image in sparse domain of original image will not have a sparse representation as much as original image sparsity. In this method we assume that the proper dictionary to achieve image in sparse domain is available
  6. Keywords:
  7. Image de-noising ; Impulsive noise ; Impulsive noise removal ; Natural images ; Noisy image ; Optimization method ; Original images ; Sparse representation ; Sparsity ; Impulse noise ; Information science ; Signal processing ; Iterative methods
  8. Source: 10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010, 10 May 2010 through 13 May 2010 ; May , 2010 , Pages 480-483 ; 9781424471676 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/5605449