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Linear motion blur parameter estimation in noisy images using fuzzy sets and power spectrum

Ebrahimi Moghaddam, M ; Sharif University of Technology | 2007

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  1. Type of Document: Article
  2. DOI: 10.1155/2007/68985
  3. Publisher: 2007
  4. Abstract:
  5. Motion blur is one of the most common causes of image degradation. Restoration of such images is highly dependent on accurate estimation of motion blur parameters. To estimate these parameters, many algorithms have been proposed. These algorithms are different in their performance, time complexity, precision,and robustness in noisy environments. In this paper, we present a novel algorithm to estimate direction and length of motion blur,using Radon transform and fuzzy set concepts. The most important advantage of this algorithm is its robustness and precision in noisy images. This method was tested on a wide range of different types of standard images that were degraded with different directions (between 0° and 180°) and motion lengths(between 10 and 50 pixels). The results showed that the method works highly satisfactory for SNR >22 dB and supports lower SNR compared with other algorithms. Copyright © 2007 Hindawi Publishing Corporation. All rights reserved
  6. Keywords:
  7. Algorithms ; Fuzzy sets ; Image reconstruction ; Mathematical transformations ; Parameter estimation ; Signal to noise ratio ; Spurious signal noise ; Motion blur ; Noisy images ; Power spectrum ; Radon transform ; Motion estimation
  8. Source: Eurasip Journal on Advances in Signal Processing ; Volume 2007 , 2007 ; 11108657 (ISSN)
  9. URL: https://asp-eurasipjournals.springeropen.com/articles/10.1155/2007/68985