Research on fusion technology based on low-light visible image and infrared image

Image fusion technology usually combines information from multiple images of the same scene into a single image so that the fused image is often more informative than any source image. Considering the characteristics of low-light visible images, this study presents an image fusion technology to improve contrast of low-light images. This study proposes an adaptive threshold-based fusion rule. Threshold is related to the brightness distribution of original images. Then, the fusion of low-frequency coefficients is determined by threshold. Pulse-coupled neural networks (PCNN)-based fusion rule is proposed for fusion of high-frequency coefficients. Firing times of PCNN reflect the amount of detail information. Thus, a high-frequency coefficient corresponding to maximum firing times is chosen as the fused coefficient. Experimental results demonstrate that the proposed method obtains high-contrast images and outperforms traditional fusion approaches on image quality. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.