Dual-Band Image Fusion Approach Using Regional Weight Analysis Combined with a Multi-Level Smoothing Filter

Abstract

Image fusion is an effective and efficient way to express the feature information of an infrared image and abundant detailed information of a visible image in a single fused image. However, obtaining a fused result with good visual effect, while preserving and inheriting those characteristic details, seems a challenging problem. In this paper, by combining a multi-level smoothing filter and regional weight analysis, a dual-band image fusion approach is proposed. Firstly, a series of dual-band image layers with different details are obtained using smoothing results. With different parameters in a bilateral filter, different smoothed results are achieved at different levels. Secondly, regional weight maps are generated for each image layer, and then we fuse the dual-band image layers with their corresponding regional weight map. Finally, by imposing proper weights, those fused image layers are synthetized. Through comparison with seven excellent fusion methods, both subjective and objective evaluations for the experimental results indicate that the proposed approach can produce the best fused image, which has the best visual effect with good contrast, and those small details are preserved and highlighted, too. In particular, for the image pairs with a size of 640 × 480, the algorithm could provide a good visual effect result within 2.86 s, and the result has almost the best objective metrics.