Technology of Graphic & Image
|
303-307

Multi-sequence satellite image cloud removal based on dense residual network

Xiao Changcheng
Wu Xi
He Yan
School of Compute Science & Technology, Chengdu University of Information Technology, Chengdu 610225, China

Abstract

The most common problem in remote sensing imagery is cloud pollution, which will lead to lack of image information and low availability of remote sensing data. To solve this problem, this paper proposed a cloud removal algorithm for multi-sequence satellite images based on dense residual network. The network used multisequence cloud satellite images as input, which could provide more timing feature information for the network and improve the effect of cloud removal. Secondly, using a dense residual layer in the middle of the network, which ensured the maximum transfer and use of feature information between the convolutional layers, so that the generated repair image as a whole structure was reasonable and the edge details were clearer. Finally, it used pixel shuffle upsample to enhance the use of spatial information and improved the repair effect. This method was verified on the European "Sentinel-2" remote sensing satellite image dataset. The peak signal-to-noise ratio and structural similarity index are 27.59 and 0.854 0, both of which exceed the original processing method STGAN of the data set, and improve the effectiveness of remote sensing image to cloud.

Foundation Support

国家重点研发计划课题(2020YFA0608001, 2017YFC1502203)
国家自然科学基金资助项目(42075142)
四川省科技计划项目(2019YFG0496,2020YFG0143,2020JDTD0020)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.05.0173
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Technology of Graphic & Image
Pages: 303-307
Serial Number: 1001-3695(2022)01-054-0303-05

Publish History

[2022-01-05] Printed Article

Cite This Article

肖昌城, 吴锡, 何妍. 基于稠密残差网络的多序列卫星图像去云 [J]. 计算机应用研究, 2022, 39 (1): 303-307. (Xiao Changcheng, Wu Xi, He Yan. Multi-sequence satellite image cloud removal based on dense residual network [J]. Application Research of Computers, 2022, 39 (1): 303-307. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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