Heterogeneous Image Fusion for Target Recognition Based on Evidence Reasoning

Shuyue Wang, Zhunga Liu, Zuowei Zhang, Yang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Multi-source fusion is an efficient strategy in complex image target recognition since it can exploit the complementary knowledge in different sources to improve the classification performance. In this paper, we propose a new end-to-end framework for heterogeneous (i.e. visible & infrared) image fusion target recognition (HIFTR). Firstly, two networks are built for the visible and infrared images respectively and jointly trained based on mutual learning. It aims to transfer heterogeneous information mutually and improve the generalization performance of the networks. Secondly, a weighted decision-level fusion method based on evidence reasoning is developed to combine the classification results of visible and infrared images for the final target recognition. In the training process, the weight of each image is automatically optimized in the networks. Finally, the performance of the proposed HIFTR has been evaluated by comparing with other related methods, and the experimental results show that the HIFTR method can efficiently improve the classification accuracy.

Original languageEnglish
Title of host publicationBelief Functions
Subtitle of host publicationTheory and Applications - 7th International Conference, BELIEF 2022, Proceedings
EditorsSylvie Le Hégarat-Mascle, Emanuel Aldea, Isabelle Bloch
PublisherSpringer Science and Business Media Deutschland GmbH
Pages153-162
Number of pages10
ISBN (Print)9783031178009
DOIs
StatePublished - 2022
Event7th International Conference on Belief Functions, BELIEF 2022 - Paris, France
Duration: 26 Oct 202228 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13506 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Belief Functions, BELIEF 2022
Country/TerritoryFrance
CityParis
Period26/10/2228/10/22

Keywords

  • Evidence reasoning
  • Heterogeneous image fusion
  • Mutual learning
  • Target recognition

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