Paper Info
Title
Coefficient-Tracking Speckle Reducing Anisotropic Diffusion
Abstract
Speckle reducing anisotropic diffusion (SRAD) filter is introduced to significantly reduce speckle noise from images. Yet, SRAD suffers from the problems of ordinary diffusion filters, e.g., objects boundaries broadening and edges dislocation.This paper provides a more robust diffusion-filtering scheme, which is based on tracking the image main features across SRAD scale-space images. Coefficient-tracking SRAD (CSRAD) controls the amount of allowed diffusion based on the edges original location.CSRAD is tested on Berkley segmentation dataset. CSRAD results are subjectively compared with those of SRAD in terms of edge localization, smoothing enhancement, and features preserving. Experimental results show that CSRAD significantly reduced the features distortion and edges dislocation effects. Consequently, the entire diffusion process is enhanced.
Year
DOI
Venue
2009
10.1007/978-3-642-02611-9_14
ICIAR
Keywords
Field
DocType
features distortion,edges dislocation,ordinary diffusion filter,edges dislocation effect,edges original location,anisotropic diffusion,csrad result,coefficient-tracking speckle,entire diffusion process,coefficient-tracking srad,srad scale-space image,edge detection,dislocations,diffusion process,noise reduction,speckle noise,coefficient of variation,scale space
Anisotropic diffusion,Noise reduction,Diffusion process,Computer vision,Speckle pattern,Computer science,Edge detection,Smoothing,Artificial intelligence,Speckle noise,Distortion
Conference
Volume
ISSN
Citations 
5627
0302-9743
0
PageRank 
References 
Authors
0.34
16
2
Name
Order
Citations
PageRank
Walid Ibrahim110618.65
Mahmoud R. El-Sakka28114.17