Adaptive selection of visual and infra-red image fusion rules

Guang Yang, Yafeng Yin, Hong Man

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

Abstract

The fusion of images captured from Electrical-Optical (EO) and Infra-Red (IR) cameras has been extensively studied for military applications in recent years. In this paper, we propose a novel wavelet-based framework for online fusion of EO and IR image sequences. The proposed framework provides multiple fusion rules for image fusion as well as a novel edge-based evaluation method to select the optimal fusion rule with respect to different practical scenarios. In the fusion step, EO and IR images are decomposed into different levels by 2D discrete wavelet transform. The wavelet coefficients at each level are combined by a set of fusion rules, such as min-max selection, mean-value, weighted summations, etc. Various fused images are obtained by inverse wavelet transform of combined coefficients. In the evaluation step, Sobel operator is applied on both the fused images and original images. Compared with original images, the remaining edge information in the fused each image is calculated as the fusion quality assessment. Finally, the fused image with the highest assessment value will be selected as the fusion result. In addition, the proposed method can adaptively select the best fusion rule for EO and IR images under different scenarios.

Original languageEnglish
Title of host publication2010 IEEE 39th Applied Imagery Pattern Recognition Workshop, AIPR 2010
DOIs
StatePublished - 2010
Event2010 IEEE 39th Applied Imagery Pattern Recognition Workshop, AIPR 2010 - Washington, DC, United States
Duration: 13 Oct 201015 Oct 2010

Publication series

NameProceedings - Applied Imagery Pattern Recognition Workshop
ISSN (Print)1550-5219

Conference

Conference2010 IEEE 39th Applied Imagery Pattern Recognition Workshop, AIPR 2010
Country/TerritoryUnited States
CityWashington, DC
Period13/10/1015/10/10

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