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                                       Details van artikel 1 van 9 gevonden artikelen
 
 
 
 
 
Titel:
Auteur: Mahmoud Saeidi
Leila Chehreghani Anzabi
Mahmoud Khaleghi
Verschenen in: International journal of signal processing, image processing and pattern recognition
Paginering: Jaargang 2 (2009) nr. 2 pagina's 75-90
Jaar: 2009
Inhoud: In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership function: Symmetrical, Continuous Function. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, is much more effective in suppressing noise and preserving edges than thepreviously reported algorithms such as [1-13]. Indeed, assigned weights to noisy pixels are very adaptive so that it well makes use of correlation of pixels. On the other hand, the motionestimation methods are erroneous and in high-density noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn’t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.
Uitgever: SERSC (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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