融合性能指标及基于提升小波变换的图像融合算法

C. Ramesh, T. Ranjith
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引用次数: 72

摘要

本文介绍了融合对称性(FS)的概念,作为评价融合算法性能的一个指标。融合对称度量量化了融合图像相对于输入图像的相对距离(根据互信息)。FS越小,融合图像就越对称,也就是说,它从两个输入图像中捕获信息。对传统的联合互信息最大化准则进行了量化,提出了融合因子的定义。提出了一种基于提升小波滤波器的图像融合算法。该算法在变换域内进行融合。将该算法的性能与基于平均和拉普拉斯金字塔的方法进行了比较,并给出了针对不同传感器条件选择合适图像融合算法的准则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fusion performance measures and a lifting wavelet transform based algorithm for image fusion
This paper introduces the concept of fusion symmetry (FS) as a measure of evaluating performance of fusion algorithms. The fusion symmetry measure quantifies the relative distance (in terms of mutual information) of the fused image with respect to input images. The smaller the FS the more symmetric is the fused image, i.e., it captures information from both the input images. The traditional criterion of maximizing the joint mutual information is also quantified and a definition called fusion factor is evolved. An algorithm for image fusion using a lifting wavelet filter is proposed. In this algorithm fusion is performed in the transformed domain. The performance of this algorithm is compared with that obtained using average, Laplacian pyramid based approaches and guidelines for selecting an appropriate image fusion algorithm for different sensor conditions are evolved.
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