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

机译:基于区域到像素的多传感器图像融合

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摘要

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.
机译:本文提出了一种基于区域的多传感器图像融合方法。在我们算法的初始阶段,通过应用3×3过滤器掩模,从输入图像中抑制噪声。在下一阶段,通过计算相似性图图像然后基于标记的流域算法来从输入图像中分割区域。此后,通过计算该区域中像素的相对重要性来融合区域。这里,该区域中的像素的相对重要性被计算为相对于整个区域的不对称或偏移的邻域中的该像素的第二中心矩。之后,基于该区域中的区域中的像素的相对重要性来实现决策图。最后,将所有熔融区域组合以产生最终融合图像。要检查我们的算法的鲁棒性,我们已经测试了来自曼彻斯特大学英国数据库中收集并与国家的最先进的一些基于区域的融合技术相比,120多传感器图像对。实验结果表明了在视觉和客观感知评估指标方面的提出方法的优越性。

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