Mr. Jun Li Profile

Jun Li

at South China Univ of Technology

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Proceedings Article | 15 November 2007 Paper

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

Jun Li, Guohua Chen, Tiejun Ma

Proceedings Volume 6786, 67864H (2007) https://doi.org/10.1117/12.751513

KEYWORDS: Speckle, Digital filtering, Fringe analysis, Denoising, Image filtering, Speckle pattern, Visualization, Nonlinear filtering, Data processing, Image processing

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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.

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