Infrared and Visible Image Fusion Based on Tetrolet Transform

Abstract

Tetrolet transform has a better directionality of the structure and can express texture features of image precisely in dealing with high-dimensional signal. This paper introduces tetrolet transform into infrared and visible images for fusion to obtain a greater amount of information. First, the tetrolet transform was performed on the images which are fused to obtain high-pass and low-pass subbands on different scales. Then, a method based on local region gradient information was applied to low-pass subbands to get the low-pass fusion coefficients. Finally, the inverse tetrolet transform was utilized to obtain fused image. Using a variety of images to perform fusion experiment, all the results have shown that the fused image has more abundant features and more amount of information by using tetrolet transform. Compared with the traditional fusion algorithms, the fusion algorithm presented in this paper provides better subjective visual effect, and the standard deviation and entropy value would be somewhat increased.