遥感影像融合AIHS转换与粒子群优化算法

doi:10.11947/j.AGCS.2019.20180509

测绘学报 ›› 2019, Vol. 48 ›› Issue (10): 1296-1304.doi: 10.11947/j.AGCS.2019.20180509

遥感影像融合AIHS转换与粒子群优化算法

陈应霞¹, 陈艳², 刘丛³

1. 华东师范大学计算机科学与软件工程学院, 上海 200062;
2. 长江大学计算机科学学院, 湖北荆州 434023;
3. 上海理工大学光电信息与计算机工程学院, 上海 200082

收稿日期:2018-11-05 修回日期:2019-03-13 出版日期:2019-10-20 发布日期:2019-10-24
通讯作者: 陈艳 E-mail:345854199@qq.com
作者简介:陈应霞(1978-),男,博士,讲师,研究方向为遥感图像处理。E-mail:672057422@qq.com
基金资助:
国家自然科学基金（61703278）

Joint AIHS and particle swarm optimization for Pan-sharpening

CHEN Yingxia¹, CHEN Yan², LIU Cong³

1. Department of Computer Science, East China Normal University, Shanghai 200062, China;
2. School of Computer Science, Yangtze University, Jingzhou 434023, China;
3. School of Computer Science, University of Shanghai for Science and Technology, Shanghai 200082, China

Received:2018-11-05 Revised:2019-03-13 Online:2019-10-20 Published:2019-10-24
Supported by:
The National Natural Science Foundation of China (No. 61703278)

摘要/Abstract

摘要： Pan-sharpening是通过将低分辨率多光谱图像（LMS）与高分辨率全色图像（PAN）进行合成而获得高光谱高空间分辨率的多光谱图像（HMS）的过程。本文提出一种Pan-sharpening方法，称为PAIHS。该方法基于自适应亮度-色度-饱和度（AIHS）转换和变分Pan-sharpening框架以及两个假设（① Pan-sharpening图像和原始多光谱图像（MS）具有相同的光谱信息；②Pan-sharpening图像与全色图像（PAN）包含的几何信息保持一致），同时确定目标函数，然后用粒子群算法（PSO）进行优化，目的是得到最佳控制参数并求得目标函数最小值，此时对应着最好的Pan-sharpening质量。试验结果表明，本文提出的方法具有高效性和可靠性，获得的性能指标也优于目前一些主流的融合方法。

关键词: Pan-sharpening, 多光谱图像, 全色图像, 亮度-色度-饱和度, 粒子群算法, 目标函数

Abstract: Pan-sharpening is a process of obtaining a high spatial and spectral multispectral image (HMS) by combining a low resolution multispectral image (LMS) with a high resolution panchromatic image (PAN). In this paper, a Pan-sharpening method called PAIHS is proposed. It is based on adaptive intensity-hue-saturation (AIHS) transformation, variational Pan-sharpening framework and two assumptions:①pan-sharpened image and original multispectral image (MS) have the same spectral information; ②pan-sharpened image and PAN image contain the same geometric information. The suitable objective function was established, and optimized by particle swarm optimization (PSO) to obtain the optimal control parameters and minimum value, which corresponds to the best Pan-sharpening quality. The experimental results show that the proposed method has high efficiency and reliability, and the obtained performance index is also better than some of the current mainstream fusion methods.

Key words: Pan-sharpening, multispectral image, panchromatic image, AIHS transformation, particle swarm optimization, objective function

中图分类号:

P237

陈应霞, 陈艳, 刘丛. 遥感影像融合AIHS转换与粒子群优化算法[J]. 测绘学报, 2019, 48(10): 1296-1304.

CHEN Yingxia, CHEN Yan, LIU Cong. Joint AIHS and particle swarm optimization for Pan-sharpening[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(10): 1296-1304.

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遥感影像融合AIHS转换与粒子群优化算法

Joint AIHS and particle swarm optimization for Pan-sharpening

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