基于多指标提取与组合的多焦点图像性能评价方法

Weitong Li, Yu Cheng, Yuehui Sun, Shaoqiu Xu
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引用次数: 1

摘要

在多焦点图像融合中,提出了一些客观的指标来评价融合后的图像,并进一步比较了相应的融合算法。对于一幅图像,一些指标可以得到满意的结果,而另一些指标则不能给出可信的结论。单一的客观指标无法对图像进行正确、全面的评价,因此可以将多个指标结合起来对融合后的图像进行评价。本文研究了一种多指标的提取与组合方法。首先,形成了一个包含一些被广泛引用和具有代表性的指标的总集合。其次,对于每组图像,从总集合中提取适当的度量来构建评估集。因此两组图像可能有不同的评价集。第三,对于同一组的每张图像,将提取的度量分别组合成三个标量,分别使用三种测量方法。最后用标量验证了测量结果的一致性。仿真结果表明,该方法优于单一度量方法,为性能评价的研究提供了新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-focus Image Performance Evaluation Method Based on the Extraction and Combination of Multiple Metrics
In multi-focus image fusion, some objective metrics were proposed to evaluate the fused images and compare the corresponding fusion algorithms further. For an image, some metrics can acquire satisfied results, while others can't give credible conclusions. Single objective metric can't assess an image correctly and comprehensively, so multiple metrics may be combined to evaluate the fused images. In this paper, a method named multiple metrics extraction and combination is studied. First, a total set with some popularly cited and representative metrics is formed. Second, for each group of images, the appropriate metrics are extracted from the total set to construct an evaluation set. Therefore two sets of images may have diverse evaluation sets. Third, for each image of the same group, the extracted metrics are combined into three scalars with three measurement methods respectively. Finally, the consistency of measurement results is verified with the scalars. The simulations show that our method outperforms single metric and provides a new way to the research of performance evaluation.
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