Title :
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
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;
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
DOI :
10.1109/IMCCC.2014.132
