A new FCM based on simulated annealing of hyperspectral image compression

被引：0

作者：

Zhao, Xue-Jun ^{[1
]}

Wang, Xiao-Juan ^{[1
]}

Yu, Kai-Min ^{[1
]}

Qiao, Xu ^{[1
]}

机构：

[1] School of Mechanical Electronic and Information Engineering, China University of Mining and Technology (Beijing), Beijing

来源：

Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2015年 / 38卷 / 05期

关键词：

Dimension reduction; Fuzzy C-means clustering; Simulated annealing; The elbow; Vector quantization;

D O I：

10.13190/j.jbupt.2015.05.010

中图分类号：

学科分类号：

摘要：

Lossy compression of hyperspectral image based on vector quantization algorithms can achieve a high compression ratio, but it is of time complexity and great distortion. This article proposed a new fuzzy C-means clustering (FCM) algorithm based on simulated annealing. Firstly, the dimensions were reduced by using the algorithm of adaptive band combination dimensional reduction (ABC), then the number of clusters with the elbow was determined. FCM was combined with simulated annealing, and found optimal result quickly, then recovered dimensions. We got optimization coding by deblurring U. Through this approach, the efficiency has been improved and the distortions have been reduced greatly. © 2015, Beijing University of Posts and Telecommunications. All right reserved.

引用

页码：58 / 61and70

页数：6112

共 9 条

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