Multi-sensor Image Decision Level Fusion Detection Algorithm Based on D-S Evidence Theory

Author

Aili Wang ; Jinna Jiang ; Haoye Zhang

Author_Institution

Higher Educ. Key Lab. for Meas. & Control Technol. & Instrumentations of Heilongjiang, Harbin Univ. of Sci. & Technol., Harbin, China

fYear

2014

fDate

18-20 Sept. 2014

Firstpage

620

Lastpage

623

Abstract

Fusing the image information obtained by different sensors could make full use of all sensor information. D-S evidence theory is popular in fusion field. Aim to multi-sensor target detecting, we give the algorithm of mass function on D-S evidence theory, using the combination rule to combinate the three evidences of local variance offset, local variance contrast and local entropy of infrared and visible images. The experimental results on select images, which are marked by different color to discriminate different detection results, demonstrate its usefulness.

Keywords

image fusion; inference mechanisms; D-S evidence theory; image information fusion; local entropy; mass function; multisensor image decision level fusion detection algorithm; multisensor target detection; sensor information; Detection algorithms; Entropy; Feature extraction; Image fusion; Object detection; Sensors; Uncertainty; D-S theory of evidence; image fusion; local entropy Introduction; local variance contrast; local variance offset;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 2014 Fourth International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4799-6574-8

Type

conf

DOI

10.1109/IMCCC.2014.132

Filename

6995102