论文标题
基于差异差异的边缘地图质量度量
Just-Noticeable-Difference Based Edge Map Quality Measure
论文作者
论文摘要
通过有效的边缘地图质量度量，可以提高边缘检测器的性能。已经提出了几种评估方法，导致同一候选边缘图的性能得分不同。但是，有效的措施是可以自动化的措施，并且与人类判断的边缘图质量相关。基于距离的边缘地图措施广泛用于评估边缘图质量。这些方法考虑边缘像素的距离和统计特性以估计性能得分。现有方法可以自动化；但是，它们缺乏感知特征。本文基于人类视觉系统的差异差异（JND）的特征，介绍了边缘地图质量度量，以补偿基于距离的边缘测量的缺点。为此，我们设计了恒定的刺激实验，以测量两个空间替代方案的JND值。实验结果表明，根据主观评估，基于JND的距离计算优于现有的基于距离的措施。
The performance of an edge detector can be improved when assisted with an effective edge map quality measure. Several evaluation methods have been proposed resulting in different performance score for the same candidate edge map. However, an effective measure is the one that can be automated and which correlates with human judgement perceived quality of the edge map. Distance-based edge map measures are widely used for assessment of edge map quality. These methods consider distance and statistical properties of edge pixels to estimate a performance score. The existing methods can be automated; however, they lack perceptual features. This paper presents edge map quality measure based on Just-Noticeable-Difference (JND) feature of human visual system, to compensate the shortcomings of distance-based edge measures. For this purpose, we have designed constant stimulus experiment to measure the JND value for two spatial alternative. Experimental results show that JND based distance calculation outperforms existing distance-based measures according to subjective evaluation.
