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ANALYSIS OF THE CLUSTERING FUSION ALGORITHM FOR MULTI-BAND COLOR IMAGE

文献类型： 外文期刊

作者： Fan, Jiangchuan 1 ; Guo, Xinyu 1 ; Du, Jianjun 1 ; Wen, Weiliang 1 ; Lu, Xianju 1 ; Louiza, Brahmani 4 ;

作者机构： 1.Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

3.Beijing Key Lab Digital Plant, Beijing 100097, Peoples R China

4.Univ North Carolina Greensboro, Dept Math & Stat, Greensboro, NC 27402 USA

关键词： Multi-band; color image; cluster fusion

期刊名称：DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES S （ 影响因子：2.425； 五年影响因子：1.49 ）

ISSN： 1937-1632

年卷期： 2019 年 12 卷 4-5 期

页码：

收录情况： SCI

摘要： Because of the limitations of the technical conditions, the traditional algorithms can not be mapped with many kinds of color, and the treatment effect is poor, which is not conducive to human eye observation. A clustering fusion algorithm based on D-S evidence theory is proposed in this paper to make salt denoising and Gauss denoising operation for the multi-band color image, to improve the image recognition, and better reflect the objective reality, which is not limited by technical conditions; the denoised images are made texture features and edge features extraction; these two kinds of features are fused and carried out the probability distribution to solve the probability of that the each pixel belongs to each class; Based on the DS evidence combination, the probability of four channels is fused, and according to the probability of what kind of each pixel belonging is the largest, it is clustered. Experimental results show that the proposed algorithm can combine different bands of color images to different levels of target features, and retain more effective information, which is conducive to target recognition and detection.

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