Contrast pyramid based image fusion scheme for infrared image and visible image
In this research, a new fusion scheme based on improved regional energy contrast pyramid algorithm with respect to the human visual characteristics is presented, the infrared and visible data from HJ1-B satellite, ASTER were performed in the experiments. First of all, the source data are decomposed by contrast pyramid transform. Second, the regional energy, standard deviation and similarity were calculated, then the regional fusion operator was determined by threshold and standard deviation. Finally, the fused image was reconstructed by inverse contrast pyramid transform. Moreover, the improved regional energy contrast pyramid based, Laplacian Pyramid based, Gradient Pyramid based and Wavelet based image fusion algorithms were evaluated and compared by means of the fusion evaluation indexes, namely the entropy, root mean square error and PSNR. The experimental results showed that the image fusion algorithm proposed in this research is more effective.