Application of weighted image fusion based on compressed sensing in thermal fault monitoring
XIAO Er liang, HUANG Yuan song
（School of Optical Electrical and Computer Engineering, University of Shanghai For Science 
and Technology, Shanghai 200093,China）


Abstract: Aiming at the problems of large date in color image fusion of the thermal fault location of electrical equipment, researches and inductions were made for the color image fusion and compressed sensing theory, a kind of infrared and visible color image fusion algorithm based on compressed sensing was proposed. Firstly, the infrared thermal image and visible color image date was decomposed into three channels of R, G, B, each channel of the date was represented by wavelet basis. Secondly, Gauss random matrix was used to sample the sparse data and get the measured value, the measurement value of the corresponding channel was fused by the weighting factors. Finally, the orthogonal matching pursuit reconstruction algorithm (OMP) was performed to reconstruct the fusion data of each channel, the reconstruction data was restored to the color fused image. The results indicate that the proposed algorithm can achieve fusion with less than 50% of the sample points. The value of AG, PSNR, SF, IE is close to the index of traditional data fusion, which maintaines the information of high temperature area and background area perfectly.

Key words: image fusion; thermal image; visible image; compressed sensing; thermal fault