Pan-sharpening via regional division and NSST

被引：0
作者：
Cheng Shi
Fang Liu
Qiguang Miao
机构：
[1] Xidian University,School of Computer Science and Technology
[2] Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education,International Research Center for Intelligent Perception and Computation
[3] Xidian University,undefined
来源：
Multimedia Tools and Applications | 2015年 / 74卷
关键词：
Pan-sharpening; NSST; Regional division; Similarity measure;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a novel Pan-sharpening algorithm for high resolution Panchromatic (HR PAN) and low resolution multispectral image (LR MS) via regional division and Non-sampled shift-invariance shearlet transform (NSST) is proposed. The purpose of our algorithm is to fuse the LR MS and the HR PAN image for different objects respectively, in order to solve the spectral distortion and spatial resolution problems in the Pan-sharpened image. Firstly, the LR MS and the HR PAN images are divided into structure and non-structure regions respectively, and a regional association map is set according to the division result. A regional similarity measure, degree of regional match (DRM), is proposed to evaluate the correction of the two regions. And a fusion rule is designed based on DRM. Because of the flexibility direction features, NSST can represent the edge information of the image better. Hence the LR MS and the HR PAN images are decomposed by the NSST, and the Pan-sharpened image can be obtained by the designed rule. Experimental results have proved that the proposed algorithm has a better Pan-sharpening result than other methods do.
引用
收藏
页码：7843 / 7857
页数：14
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