GGRNet : Global Graph Reasoning Network for Salient Object Detection in Optical Remote Sensing Images

Xuan LIU, Yumo ZHANG, Runmin CONG*, Chen ZHANG, Ning YANG, Chunjie ZHANG, Yao ZHAO

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

5 Citations (Scopus)

Abstract

The task of salient object detection (SOD) in optical remote sensing images (RSIs) is more challenging than the SOD in natural sensing images (NSIs) because of the unique characteristics of remote sensing images such as various object scales and background context redundancy. However, the existing methods ignore the global relationship modeling between different salient objects or different parts in one salient object. To this end, we design a Global Graph Reasoning Module (GGRM) in a lightweight and effective form, and propose a novel Global Graph Reasoning Network (GGRNet) for SOD in optical RSIs. During the graph reasoning, the GGRM considers the role of the global information. Specifically, we explore two ways to utilize the global information, including the global features and global nodes, which are ingeniously added to the interaction of graph nodes and fully integrated through iteration. Besides, we stabilize the projection channel between coordinate space and interactive space through an attention mechanism. The GGRNet outperforms the existing state-of-the-art SOD algorithms on two publicly available datasets, and the number of parameters is only 25.01 Mb.

Original languageEnglish
Title of host publicationPattern Recognition and Computer Vision : 4th Chinese Conference, PRCV 2021, Proceedings, Part II
EditorsHuimin MA, Liang WANG, Changshui ZHANG, Fei WU, Tieniu TAN, Yaonan WANG, Jianhuang LAI, Yao ZHAO
PublisherSpringer Science and Business Media Deutschland GmbH
Pages584-596
Number of pages13
ISBN (Electronic)9783030880071
ISBN (Print)9783030880064
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021 - Beijing, China
Duration: 29 Oct 20211 Nov 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13020
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2021
Country/TerritoryChina
CityBeijing
Period29/10/211/11/21

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

  • Global information
  • Graph reasoning
  • Optical remote sensing images
  • Salient object detection

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