A false color image fusion method based on multi-resolution color transfer in normalization YCBCR space

In this paper, a false color image fusion method for merging visible and infrared images is proposed. Firstly, the source images and reference image are decomposed respectively by Laplacian pyramid transform. Then the grayscale fused image and the difference images between the normalized source images are assigned to construct YCBCR components. In the color transfer step, all the three channels of the color space in each decomposition level are processed with the statistic color mapping according to the color characteristics of the corresponding sub-images of the reference image. Color transfer is designed based on the multi-resolution scheme in order to significantly improve the detailed information of the final image, and to reduce excessive saturation phenomenon to have a comparatively natural color appearance compared with the classical global-coloring algorithm. Moreover, the differencing operation between the normalized source images not only provides inter-sensor contrast to make popping the potential targets but also weakens the influence of the ambient illumination variety to a certain degree. Finally, the fused results and several metrics for evaluation of fused images subjectively and objectively illustrate that the proposed color image fusion algorithm can yield a more complete mental representation of the perceived scene, resulting in better situational awareness.