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A fast iterative method for removing sparse noise from sparse signals

Sadrizadeh, S ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/GlobalSIP45357.2019.8969112
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. Reconstructing a signal corrupted by impulsive noise is of high importance in several applications, including impulsive noise removal from images, audios and videos, and separating texts from images. Investigating this problem, in this paper we propose a new method to reconstruct a noise-corrupted signal where both signal and noise are sparse but in different domains. We apply our algorithm for impulsive noise (Salt- and-Pepper Noise (SPN) and Random-Valued Impulsive Noise (RVIN) removal from images and compare our results with other notable algorithms in the literature. Simulation indicates show that our algorithm is not only simple and fast, but also it outperforms the other state-of-the-art methods in terms of reconstruction quality and/or complexity. © 2019 IEEE
  6. Keywords:
  7. Adaptive thresholding ; Impulsive noise ; Iterative method ; Sparse signal ; Impulse noise ; Iterative methods ; Salt removal ; Signal reconstruction ; Corrupted signals ; Different domains ; Impulsive noise removal ; Reconstruction quality ; Salt-and-pepper noise ; Sparse signals ; State-of-the-art methods ; Image denoising
  8. Source: 7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019, 11 November 2019 through 14 November 2019 ; 2019 ; 9781728127231 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/8969112