基于边缘保持滤波和结构张量的遥感图像融合

doi:10.13700/j.bh.1001-5965.2018.0345

北京航空航天大学学报 ›› 2018, Vol. 44 ›› Issue (12): 2479-2488.doi: 10.13700/j.bh.1001-5965.2018.0345

基于边缘保持滤波和结构张量的遥感图像融合

曲家慧, 李云松, 董文倩, 郑毓轩

西安电子科技大学综合业务网国家重点实验室, 西安 710071

收稿日期:2018-06-11 修回日期:2018-07-27 出版日期:2018-12-20 发布日期:2018-12-28
通讯作者: 李云松 E-mail:ysli@mail.xidian.edu.cn
作者简介:曲家慧,女,博士研究生。主要研究方向:高光谱遥感图像处理、机器学习、神经网络;李云松,男,博士,教授,博士生导师。主要研究方向:图像视频压缩编码、图像处理、高性能计算、芯片设计。
基金资助:
国家自然科学基金（61502367，61501346，61701360，61571345，91538101）；高等学校学科创新引智计划（"111计划"）（B08038）；长江学者特聘教授支持计划（CJT160102）；中央高校基本科研业务费专项资金；西安电子科技大学研究生创新基金

Remote sensing image fusion based on edge-preserving filtering and structure tensor

QU Jiahui, LI Yunsong, DONG Wenqian, ZHENG Yuxuan

State Key Laboratory of Integrated Service Network, Xidian University, Xi'an 710071, China

Received:2018-06-11 Revised:2018-07-27 Online:2018-12-20 Published:2018-12-28
Supported by:
National Natural Science Foundation of China (61502367, 61501346, 61701360, 61571345, 91538101); 111 Project (B08038); Yangtze River Scholar Bonus Schemes of China (CJT160102); the Fundamental Research Funds for the Central Universitiesl; Innovation Fund of Xidian University

摘要/Abstract

摘要： 高光谱（HS）遥感图像含有丰富的光谱信息，但是空间分辨率较低，而全色（PAN）遥感图像空间分辨率较高。针对高光谱遥感图像与全色遥感图像的融合问题，提出了一种新的基于边缘保持滤波和结构张量的遥感图像融合算法。首先，为了提取高光谱遥感图像的空间信息，提出使用边缘保持滤波方法，该提取方法可以保证提取的信息全部为空间细节信息，避免低频混叠。其次，对全色遥感图像采用高斯-拉普拉斯图像增强算法进行图像锐化，降低图像噪声，锐化细节信息。再次，为得到总空间信息，提出使用结构张量的自适应加权策略。传统的融合算法通常仅从全色遥感图像中提取空间信息，可能会引起光谱失真或空间细节加入不足等问题，为了克服这些问题，提出的自适应加权策略得到的总空间信息不仅包含全色遥感图像的空间信息，还包含高光谱遥感图像的空间信息，且自适应加权相对于全局常数加权，可以自动选取更加合适的加权数据。最后，通过构建可以控制光谱和空间失真的增益矩阵，将总空间信息注入到插值的高光谱遥感图像的每个波段中，得到融合的高光谱图像。实验结果表明，本文提出的遥感图像融合算法，在客观评价方面，取得了最优的空间和光谱性能，在视觉效果上，与其他融合算法相比，可以更有效地提高空间分辨率和保持光谱信息。

关键词: 遥感图像, 高光谱(HS)图像, 全色(PAN)图像, 图像融合, 结构张量, 边缘保持滤波

Abstract: The hyperspectral (HS) remote sensing image which contains abundant spectral information generally has low spatial resolution. While the panchromatic (PAN) remote sensing image has high spatial resolution. In order to fuse the HS and PAN remote sensing images, a new fusion algorithm based on edge-preserving filtering and structure tensor is proposed. First, to avoid low-frequency aliasing, an edge-preserving filter is introduced to extract the spatial information of the HS image. In order to sharpen the spatial information of the PAN image, an image enhancement approach is applied to the PAN image. Then, an adaptive weighting strategy which is based on the structure tensor is proposed to obtain the total spatial information. The presented adaptive weighting strategy which is different from the traditional fusion method reduces the spectral distortion and provides adequate spatial information. The injection matrix is finally constructed to reduce spectral and spatial distortion, and the fused image is generated by injecting the complete spatial information. Experimental results demonstrate that the proposed method provides more spatial information and preserves more spectral information compared with the state-of-art fusion methods.

Key words: remote sensing image, hyperspectral (HS) image, panchromatic (PAN) image, image fusion, structure tensor, edge-preserving filtering

中图分类号:

TP751

曲家慧, 李云松, 董文倩, 郑毓轩. 基于边缘保持滤波和结构张量的遥感图像融合[J]. 北京航空航天大学学报, 2018, 44(12): 2479-2488.

QU Jiahui, LI Yunsong, DONG Wenqian, ZHENG Yuxuan. Remote sensing image fusion based on edge-preserving filtering and structure tensor[J]. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2018, 44(12): 2479-2488.

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基于边缘保持滤波和结构张量的遥感图像融合

Remote sensing image fusion based on edge-preserving filtering and structure tensor

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