自相似性和边缘保持分解的超分辨率重建算法

doi:10.13474/j.cnki.11-2246.2022.0203

测绘通报 ›› 2022, Vol. 0 ›› Issue (7): 54-59.doi: 10.13474/j.cnki.11-2246.2022.0203

自相似性和边缘保持分解的超分辨率重建算法

郑艳¹, 何欢², 卜丽静³, 金鑫⁴

1. 广东工贸职业技术学院测绘遥感信息学院, 广东广州 510510;
2. 辽宁工程技术大学测绘与地理科学学院, 辽宁阜新 123000;
3. 湘潭大学自动化与电子信息学院, 湖南湘潭 411100;
4. 北京城建勘测设计研究院有限责任公司, 北京 100101

收稿日期:2021-09-07 出版日期:2022-07-25 发布日期:2022-07-28
通讯作者: 卜丽静。E-mail:478343122@qq.com
作者简介:郑艳(1979—),女,博士,工程师,研究方向为工程测量、教学科研等。E-mail:3093415@qq.com
基金资助:
国家自然科学基金青年科学基金(41801294);广东省教育厅2021年度广东省普通高校特色创新类项目(2021KTSCX207)

Super-resolution reconstruction method based on self-similarity and edge-preserving decomposition

ZHENG Yan¹, HE Huan², BU Lijing³, JIN Xin⁴

1. Department of Information Engineering in Surveying Mapping Science and Remote Sensing, Guangdong Polytechinc of Industry and Commerce, Guangzhou 510510, China;
2. School of Geomatics, Liaoning Technical University, Fuxin 123000, China;
3. College of Automation and Eletronic Information, Xiangtan University, Xiangtan 411100, China;
4. Beijing Urban Construction Exploration & Surveying Design Research Institute Co., Ltd., Beijing 100101, China

Received:2021-09-07 Online:2022-07-25 Published:2022-07-28

摘要/Abstract

摘要： 针对目前遥感图像超分辨率重建中存在边缘细节信息重建效果不佳的问题,本文提出了—种自相似性特征和边缘特征保持分解的超分辨率重建方法。首先,为了充分利用原始低分辨率图像自身的相似性信息,通过局部自相似性重建方法得到图像的初始重建结果;然后,为进一步增加不同尺度的边缘信息,采用加权最小二乘法对初始重建结果进行多尺度边缘保持分解,并对分解的细节层进行加权线性组合;最后,通过优化计算,得到融合多尺度边缘、细节信息及局部相似性特征的超分辨率重建图像。利用多组仿真和遥感卫星图像进行对比试验。结果表明,该方法可有效提升遥感图像的边缘信息和细节信息。

关键词: 自相似性, 边缘保持分解, 超分辨率重建, 细节信息

Abstract: In view of the poor effect of edge detail information reconstruction in remote sensing image super-resolution reconstruction, a super-resolution reconstruction method based on self similarity feature and edge feature preserving decomposition is proposed. Firstly, in order to make full use of the similarity information of the original low resolution image, the local self similarity reconstruction method is used to obtain the initial reconstruction results of the image. In order to further increase the edge information of different scales, the weighted least square method is used to decompose the initial reconstruction results, and the decomposed detail layers are weighted linear combined. Finally, the super-resolution reconstructed image integrating multi-scale edge, detail information and local similarity features is obtained through optimization calculation. The results show that this method can effectively improve the edge information and detail information of remote sensing images.

Key words: self-similarity, edge-preserving decomposition, super-resolution reconstruction, detail information

中图分类号:

P237

郑艳, 何欢, 卜丽静, 金鑫. 自相似性和边缘保持分解的超分辨率重建算法[J]. 测绘通报, 2022, 0(7): 54-59.

ZHENG Yan, HE Huan, BU Lijing, JIN Xin. Super-resolution reconstruction method based on self-similarity and edge-preserving decomposition[J]. Bulletin of Surveying and Mapping, 2022, 0(7): 54-59.

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自相似性和边缘保持分解的超分辨率重建算法

Super-resolution reconstruction method based on self-similarity and edge-preserving decomposition

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