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AN IMPROVED PCA FUSION METHOD BASED ON GENERALIZED INTENSITY-HUE-SATURATION FUSION TECHNIQUE

文献类型： 外文期刊

作者： Ren, Dong 1 ; Liu, Yanmei 1 ; Yang, Xiaodong 2 ; Wang, Jihua 2 ; Yu, Haiyang 1 ;

作者机构： 1.China Three Gorges Univ, Coll Comp & Informat Technol, Yichang 443002, Hubei, Peoples R China

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

关键词： IHS-Like;PCA;image fusion;compressed domain;remote sensing

期刊名称：INTELLIGENT AUTOMATION AND SOFT COMPUTING （ 影响因子：1.647； 五年影响因子：1.469 ）

ISSN： 1079-8587

年卷期： 2012 年 18 卷 8 期

页码：

收录情况： SCI

摘要： Among various image fusion methods, principal component analysis (PCA) technique is capable of quickly merging the massive volumes of data. For lKONOS imagery, PCA can yield satisfactory "spatial" enhancement but may introduce spectral distortion, appearing as a change in colors between compositions of resembled and fused multi-spectral bands. To solve this problem, a fast improved PCA fusion method based on Intensity Hue Saturation Fusion Technique with Spectral Adjustment is presented. The experimental results demonstrate that the proposed approach can provide better performance than the original PCA method both in processing speed and image quality.

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