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blur-identification
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Blur identification in noisy images using radon transform and power spectrum modeling
, Article IWSSIP 2005 - 12th International Workshop on Systems, Signals and Image Processing(SSIP-SPI, 2005), Chalkida, 22 September 2005 through 24 September 2005 ; 2005 , Pages 347-352 ; 0907776205 (ISBN); 9780907776208 (ISBN) ; Jamzad, M ; Sharif University of Technology
2005
Abstract
Motion blur is one of the most common blurs that degrades images. Restoration of such images are highly dependent to estimation of motion blur parameters. Many researchers since 1976 have developed algorithms to estimate linear motion blur parameters. These algorithms are different in their performance, time complexity, precision and their robustness in noisy environments. In this paper we have presented a novel algorithm to estimate linear motion blur parameters such as direction and extend by using Radon transform to find direction and power spectrum modeling to find its extend. The most benefit of this algorithm is its robustness and precision in noisy images. This algorithm is a...
Motion blur identification in noisy images using mathematical models and statistical measures
, Article Pattern Recognition ; Volume 40, Issue 7 , 2007 , Pages 1946-1957 ; 00313203 (ISSN) ; Jamzad, M ; Sharif University of Technology
2007
Abstract
Motion blur is one of the most common blurs that degrades images. Restoration of such images is highly dependent on estimation of motion blur parameters. Since 1976, many researchers have developed algorithms to estimate linear motion blur parameters. These algorithms are different in their performance, time complexity, precision and robustness in noisy environments. In this paper, we have presented a novel algorithm to estimate linear motion blur parameters such as direction and length. We used Radon transform to find direction and bispectrum modeling to find the length of motion. Our algorithm is based on the combination of spatial and frequency domain analysis. The great benefit of our...