An Infrared and Visible Image Fusion Method Guided by Saliency and Gradient Information

Infrared and visible image fusion is a hot topic due to the perfect complementarity of their information. There are two key problems in infrared and visible image fusion. One is how to extract significant target areas and rich texture details from the source images, and the other is how to integrate them to produce satisfactory fused images. To tackle these problems, we propose a novel fusion framework in this paper. A multi-level image decomposition method is used to obtain the base layer and detail layer of the source image. For the fusion of base layer, an ingenious fusion strategy guided by the saliency map of source image is designed to improve the intensity of salient targets and the visual quality of the fused image. For the fusion of detail layer, an efficient approach by introducing the enhanced gradient information is presented to boost the detail features and sharpen the edges of the fused image. Experimental results demonstrate that, compared with fifteen classical and advanced fusion methods, the proposed image fusion framework has better performance in both subjective and objective evaluation.

Automated summary

A novel fusion framework for infrared and visible image fusion is proposed in this paper, which utilizes a multi-level image decomposition method to obtain base and detail layers of the source image, and introduces innovative fusion strategies and efficient approaches for handling these layers. Experimental results demonstrate the superior performance of the proposed framework compared to fifteen classical and advanced fusion methods.