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所属单位：电子信息工程学院

发表刊物：2017 2ND INTERNATIONAL CONFERENCE ON MULTIMEDIA AND IMAGE PROCESSING (ICMIP)

关键字：remote sensing image enhancement non-subsampled shearlet transform (NSST) fuzzy sets multi-stages particle swarm optimization (MSPSO) Bayesian threshold method

摘要：To further improve the definition and contrast of remote sensing images, a method of remote sensing image enhancement in non-subsampled shearlet transform (NSST) domain is proposed based on multi-stages particle swarm optimization (MSPSO) algorithm and fuzzy sets. Firstly, the image to be enhanced is decomposed into a low-frequency sub-band and several high-frequency sub-bands through NSST. Secondly, the coefficients of high-frequency sub-bands are enhanced according to adaptive Bayesian threshold method and nonlinear gain function, while that of the low-frequency sub-band is processed by using the fuzzy enhancement method with its fuzzy parameters optimized by MSPSO algorithm. A comparison is made among the proposed method, bidirectional histogram equalization method, stationary wavelet transform method, non-subsampled contourlet transform (NSCT) adaptive threshold method and artificial bee colony (ABC) optimization method in NSCT domain in terms of the subjective visual effect and objective quantitative evaluation indices such as contrast gain, definition gain and information entropy. Experimental results show that the method proposed in this paper can effectively improve the contrast and definition of remote sensing images and enhance edges details with better visual effect.

是否译文：否

发表时间：2017-01-01

合写作者：盛东慧

通讯作者：吴一全