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FD: A feature difference based image clutter metric for targeting performance

机译：FD：基于特征差异的图像杂乱指标，可提高目标性能

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摘要

Previous image clutter metrics were proposed based on the sensitivity of human visual perception to one feature of image. In this paper, a novel feature difference based image clutter metric is proposed by fully considering low-level image features, such as step edges, lines and Mach bands. As phase congruency is an invariant property of image features, the phase congruency (PC) is used to quantify the feature difference between the target and clutter images. Because PC is invariant to changes in image contrast while human visual perception is sensitive to contrast changes, a directional contrast (DC) feature is developed to calculate the contrast difference between the two images. Then we utilize the DC of the target image as an information content weighting measure to pool the local difference map to be a clutter metric. Comparative experiments demonstrate that this clutter metric correlates stronger with detection probabilities, false alarm probabilities and mean search times than previously proposed metrics.
机译：基于人类视觉感知对图像特征的敏感性，提出了先前的图像混乱度量。在本文中，通过充分考虑低级图像特征（如台阶边缘，线条和马赫带），提出了一种基于特征差异的新颖图像杂散度量。由于相位一致性是图像特征的不变属性，因此相位一致性（PC）用于量化目标图像和杂波图像之间的特征差异。由于PC对图像对比度的变化不变，而人的视觉感知对对比度的变化敏感，因此开发了方向对比度（DC）功能来计算两个图像之间的对比度差异。然后，我们将目标图像的DC作为信息内容加权度量，以将局部差异图合并为杂乱度量。比较实验表明，该杂乱度量与检测概率，虚警概率和平均搜索时间的关联性比以前提出的度量强。

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