DocumentCode
1932065
Title
A New Algorithm for Speckle Suppression using Mathematical Morphology and Adaptive Weighted Technique
Author
Jiang, Li-Hui ; Jin, Zhen-Ni ; Zhang, Fan ; Liu, Rui-Hua
Author_Institution
Civil Aviation Univ. of China, Tianjin
Volume
5
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
2427
Lastpage
2430
Abstract
In this paper, a new morphological image-cleaning algorithm that preserves thin features while removing speckle noise is presented and analyzed. In this new algorithm, the multi-scale top-hat transformation and bottom-hat transformation are added into the conventional multi-scale morphological opening and closing filtering. It differs from previous morphological filters in which it uses residual images to extract and smooth the features. The coefficients of the multi-scale top-hat transformation and bottom-hat transformation are optimized by adaptive weighted technique. This paper also shows that the new filtering algorithm preserves thin features significantly and reduces the speckle index greatly. The performance of the new filtering algorithm is superior to that of the conventional filtering methods.
Keywords
feature extraction; image enhancement; mathematical morphology; speckle; adaptive weighted technique; feature extraction; image enhancement; image filtering algorithm; mathematical morphology; morphological image-cleaning algorithm; multiscale top-hat/bottom-hat transformation; speckle suppression; Algorithm design and analysis; Cybernetics; Filtering algorithms; Filters; Machine learning; Machine learning algorithms; Morphology; Noise reduction; Signal processing algorithms; Speckle; Adaptive weighted technique; Filtering; Mathematical morphology; Multi-scale; Residual images;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370553
Filename
4370553
Link To Document