Speckle noise reduction based on the theory of rough set and entropy

Jun Li; Guohua Chen; Tiejun Ma

doi:10.1117/12.751513

15 November 2007 Speckle noise reduction based on the theory of rough set and entropy

Jun Li, Guohua Chen, Tiejun Ma

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67864H (2007) https://doi.org/10.1117/12.751513
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

A new effective algorithm of speckle noise reduction was presented in the paper, which took the characteristics of the multiplicative of speckle noise and the complexity of fringe pattern into account explicitly. The relationship expressions are deduced between intensity and speckle noise from the intensity distribution of speckle pattern, which indicates that the intensity ratio is equivalent to the speckle noise ratio in a neighborhood. Due to the complexity and correlativity of fringe pattern information, it leads to the problems of uncertainties during the information processed, the algorithm of speckle noise reduction was built based on exponent entropy, and the approximation precision based on rough set was considered in order to preserve the detail information very well. The presented method has a preferable performance based on the integrated visual and quantitative comparison. Because the filter parameters are adaptively determined by the speckle noise coefficient in the local window, the presented method was able to remove the noise in fringe pattern, and simultaneously preserve its edge effectively. The presented algorithm is effective for the laser speckle noise of fringe pattern particularly.

Citation Download Citation

Jun Li, Guohua Chen, and Tiejun Ma "Speckle noise reduction based on the theory of rough set and entropy", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67864H (15 November 2007); https://doi.org/10.1117/12.751513

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