Orientation variance as a quantifier of structure in texture
Orientation variance as a quantifier of structure in texture
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DOI：
10.1163/156856899x00012
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发表时间：
1999-01-01
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影响因子：
--
通讯作者：
Dakin, SC
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文献类型：
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作者：
Dakin, SC
我考虑了结构是如何从包含空间方向变化的纹理中得到的，并提出多局部方向方差(一系列离散图像区域的平均方向方差)是对组织程度的估计，这对于空间尺度选择和区分结构和噪声都是有用的。本文使用的定向纹理是玻璃图案，它包含了小范围的结构。将向玻璃图案添加噪声对结构与噪声任务的影响(Maloney等人，1987)与基于取向方差和模板匹配的判别(即，对目标的取向结构具有先验知识)进行比较。在密度非常低的情况下，方差模型很好地解释了人类数据。接下来，两个模型对可容忍方向方差的估计与人类对纹理和噪声的区分大体上一致。然而，这两个模型都不能解释受试者对平移模式比其他(如旋转)模式对噪声的耐受性较低。最后，为了研究这些结构测量如何很好地保持局部取向不连续性，我证明了嵌入玻璃图案中的非结构化点块的存在会产生足以解释人类检测的多局部取向方差的变化(Hel or和Zucker，1989)。综上所述，这些数据表明，简单的方向统计可以驱动一系列“纹理任务”，尽管抗噪性依赖于图案类型(旋转、平移等)。仍有待解释。
I consider how structure is derived from texture containing changes in orientation over space, and propose that multi-local orientation variance (the average orientation variance across a series of discrete images locales) is an estimate of the degree of organization that is useful both for spatial scale selection and for discriminating structure from noise. The oriented textures used in this paper are Glass patterns, which contain structure at a narrow range of scales. The effect of adding noise to Glass patterns, on a structure versus noise task (Maloney et al., 1987), is compared to discrimination based on orientation variance and template matching (i.e. having prior knowledge of the target's orientation structure). At all but very low densities, the variance model accounts well for human data. Next, both models' estimates of tolerable orientation variance are shown to be broadly consistent with human discrimination of texture from noise. However, neither model can account for subjects' lower tolerance to noise for translational patterns than other (e.g. rotational) patterns. Finally, to investigate how well these structural measures preserve local orientation discontinuities, I show that the presence of a patch of unstructured dots embedded in a Glass pattern produces a change in multi-local orientation variance that is sufficient to account for human detection (Hel Or and Zucker, 1989). Together, these data suggest that simple orientation statistics could drive a range of 'texture tasks', although the dependency of noise resistance on the pattern type (rotation, translation, etc.) remains to be accounted for.