Weighted gradient-based fusion for multi-spectral image with steering kernel and structure tensor

Qianqian Dong*, Zhiqiang Zhou, Bo Wang, Sun Li

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

In this paper, a novel weighted gradient-based fusion method combining structure tensor with steering kernel for multi-spectral images is proposed. The structure tensor is usually used to extract the main gradient information of a single point from the source image. However, the spatial structure information is important for human visual perception and the spatial context is an effective way of improving fusion result. Therefore we propose to use steering kernel to describe the spatial structure information of the source images, which is robust to the noise, and then use the weighted structure tensor that is combined with the steering kernel though a saliency metric in the proposed weighted gradient-based fusion method. Experimental results demonstrate that the proposed method outperforms other conventional fusion methods in term of visual comparison and quantitative assessment.

Original languageEnglish
Title of host publicationProceedings of the 33rd Chinese Control Conference, CCC 2014
EditorsShengyuan Xu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages7298-7302
Number of pages5
ISBN (Electronic)9789881563842
DOIs
Publication statusPublished - 11 Sept 2014
EventProceedings of the 33rd Chinese Control Conference, CCC 2014 - Nanjing, China
Duration: 28 Jul 201430 Jul 2014

Publication series

NameProceedings of the 33rd Chinese Control Conference, CCC 2014
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

ConferenceProceedings of the 33rd Chinese Control Conference, CCC 2014
Country/TerritoryChina
CityNanjing
Period28/07/1430/07/14

Keywords

  • multi-spectral image fusion
  • saliency metric
  • steering kernel
  • structure tensor

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