FusionJISI: A fusion algorithm based on infrared and visible images with joint involvement of source image

Abstract

The available image fusion framework pays little attention to the importance of the joint involvement of source images in the whole fusion process. Due to its significance, an approach called FusionJISI combining infrared and visible image fusion algorithms with the joint involvement of source images was proposed. Fully decomposed texture features of each source image are realized to reshape the feature extraction process of source images by pre-fusing infrared and visible images, and applying the features of pre-fused images in the spatial domain. At the same time, to overcome the imaging differences caused by different wavelengths of infrared and visible light, a method to extract targeted infrared image saliency is designed to compensate for the differences between source images. Then, infrared and visible images are used as reference objects in the fusion process, and the extracted feature and base maps are constructed to be utilized in a feature similarity function that obtains the optimal solution of the function, which then makes the fusion process turn to an optimization problem and avoids the difficulty of manually designing complex fusion strategies. Apart from the available technology, the proposed method allows the source image to take a part in the whole fusion process. Experiments on the public dataset show that the fusion strategy can balance the texture gradient of infrared and visible images in the fusion results.