Combining Infrared and Visible Images Using Novel Transform and Statistical Information

Abstract

This paper proposes a novel combining method of infrared (IR) and visible images based on a Discrete Wavelet Frame (DWF) approach. In contrast to existing methods, IR image is transformed first using statistical information of the visible image to emphasize relevant information. In a multi-scale domain, we then assign appropriate weights to each pixel of sub-band approximation images through pixel level weighted average for emphasizing relevant information of the IR image while keeping texture information of the visible image. Representative experiments show that the proposed method outperforms exiting methods in image quality.