Multi-scale Guided Image and Video Fusion: A Fast and Efficient Approach

Abstract

In this paper, we propose a general purpose, simple and fast fusion algorithm based on guided image filter. The proposed method can well combine useful source image information into the fused image supported by multi-scale image decomposition, structure transferring property, visual saliency detection, and weight map construction. Multi-scale image decomposition is appropriate to represent and manipulate image features at various scales. Structure transferring property enabled by our algorithm can induce structures of one source image into the other. A new visual saliency detection based on guided image filter introduced in this paper is able to extract significant regions from visually different images of the same scene. The choice of weight maps helped to integrate the complementary information pixel by pixel at each scale. Experimental outcomes of the proposed method are compared and analyzed with traditional and recent guided image filter-based fusion algorithms in terms of visual quality, fusion metrics and run time. In addition, to enhance fusion results further we made an effort to find a suitable image and video enhancement algorithm. The fusion performance analysis clearly indicates that the proposed method is very promising along with less run time.