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基于MTF和变分的全色与多光谱图像融合模型

周雨薇 杨平吕 陈强 孙权森

自动化学报Issue(2):342-352,11.
自动化学报Issue(2):342-352,11.DOI:10.16383/j.aas.2015.c140121

基于MTF和变分的全色与多光谱图像融合模型

Pan-sharpening Model Based on MTF and Variational Method

周雨薇 1杨平吕 2陈强 1孙权森1

作者信息

  • 1. 南京理工大学计算机科学与工程学院 南京 210094
  • 2. 解放军理工大学气象海洋学院 南京 211101
  • 折叠

摘要

Abstract

In order to provide the multispectral (MS) image with both high spectral and high spatial resolution, pan-sharpening approach introduces the spatial details of Panchromatic (Pan) band into MS band. Modulation transfer function (MTF) of MS and Pan bands is necessary for high fusion quality. This paper proposes a novel pan-sharpening model based on MTF and variational method. The energy functional of the proposed model consists of two terms. The first one is the spatial detail injection term, which injects detail information extracted from Pan band by a high-pass filter into MS image. The second one is the spectral signature preserving terms, in which a low-pass filter of “`a trous”wavelet is designed to maintain the multispectral information based on MTF of MS band. The experimental results on QuickBird/IKONOS/GeoEye datasets demonstrate that this model can produce the fused MS image with high spectral and high spatial quality. The proposed model is superior to AWLP, IHS BT, HPM-CC-PSF, NAWL and fast variational method in fusion performance.

关键词

图像融合/Pan-sharpening/调制传输函数/变分/多孔小波

Key words

Image fusion/pan-sharpening/modulation transfer function (MTF)/variational method/“`a trous”wavelet

引用本文复制引用

周雨薇,杨平吕,陈强,孙权森..基于MTF和变分的全色与多光谱图像融合模型[J].自动化学报,2015,(2):342-352,11.

基金项目

国家自然科学基金(41174164,61273251,61473310,41275029),中国航天科技集团公司航天科技创新基金资助项目(casc05131418),公益性行业(气象)科研专项(GYHY201306068),北极阁基金(BJG201209)资助@@@@Supported by National Natural Science Foundation of China (41174164,61273251,61473310,41275029), Aerospace Sci-ence and Technology Innovation Fund of China Aerospace Sci-ence and Technology Corporation (casc05131418), China Re-search and Development Special Fund for Public Welfare In-dustry (Meteorology)(GYHY201306068), and the BeiJiGe Fund (BJG201209) (41174164,61273251,61473310,41275029)

自动化学报

OA北大核心CSCDCSTPCD

0254-4156

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