A Region-to-Pixel Based Multi-sensor Image Fusion

A region based multi-sensor image fusion approach is proposed in this paper. At the initial stage of our algorithm, noise is suppressed from the input images by applying a 3 x 3 filter mask. In the next phase, regions are segmented from the input images by computing similarity map image followed by marker based watershed algorithm. Thereafter, regions are fused by computing the relative importance of a pixel in the region. Here, the relative importance of a pixel in the region is calculated as the second central moment of that pixel in the neighborhood with respect to the asymmetry or skewness of the whole region. After that a decision map is implemented based on the relative importance of a pixel in the region for fusion of the two correspondence regions. Finally, all the fused regions are combined to produce a final fused image. To check the robustness of our algorithm, we have tested it on 120 multi-sensor image pairs collected from Manchester University UK database and compared with some state-of-the-art region based fusion techniques. The experimental result shows the superiority of our proposed method in terms of visual and objective perception evaluation indexes. (C) 2013 The Authors. Published by Elsevier Ltd.