10 July 2009 A new algorithm based on adaptive wavelet shrinkage and P_M diffusion and its application in the denoising of fruit image
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Proceedings Volume 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering; 74890H (2009) https://doi.org/10.1117/12.836925
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
Agriculture Image denoising is one of important and fundamental technology in agriculture image processing. The adaptive wavelet shrinkage image denoising algorithm can determine an optimal threshold and neighbouring window size for every sub bands by the Stein's unbiased risk estimate (SURE). The P_M diffusivity completes denoising according to the direction and amplitude of gradient while as far as possible to keep the characteristic of image. A new algorithm based on P_M diffusion model and adaptive wavelet shrinkage is given through the different characteristic between those two different algorithms. This algorithm applies nonlinear diffusion to low frequency part of image decomposed by wavelet, and shrinks the wavelet coefficient by the adaptive wavelet shrinkage. Experimental results show that the new hybrid algorithm can significantly improve the denoising performances in Chinese apple image denoising.
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Ping Xu, You-rui Huang, Nana Zhao, "A new algorithm based on adaptive wavelet shrinkage and P_M diffusion and its application in the denoising of fruit image", Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74890H (10 July 2009); doi: 10.1117/12.836925; https://doi.org/10.1117/12.836925
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