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二阶视觉在图像中看到了什么?

What does second-order vision see in an image?

作者信息

Schofield A J

机构信息

Cognitive Science Research Centre, School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.

出版信息

Perception. 2000;29(9):1071-86. doi: 10.1068/p2913.

DOI:10.1068/p2913
PMID:11144820
Abstract

The human visual system is sensitive to both first-order variations in luminance and second-order variations in local contrast and texture. Although there is some debate about the nature of second-order vision and its relationship to first-order processing, there is now a body of results showing that they are processed separately. However, the amount, and nature, of second-order structure present in the natural environment is unclear. This is an important question because, if natural scenes contain little second-order structure in addition to first-order signals, the notion of a separate second-order system would lack ecological validity. Two models of second-order vision were applied to a number of well-calibrated natural images. Both models consisted of a first stage of oriented spatial filters followed by a rectifying nonlinearity and then a second set of filters. The models differed in terms of the connectivity between first-stage and second-stage filters. Output images taken from the models indicate that natural images do contain useful second-order structure. Specifically, the models reveal variations in texture and features defined by such variations. Areas of high contrast (but not necessarily high luminance) are also highlighted by the models. Second-order structure--as revealed by the models--did not correlate with the first-order profile of the images, suggesting that the two types of image 'content' may be statistically independent.

摘要

人类视觉系统对亮度的一阶变化以及局部对比度和纹理的二阶变化都很敏感。尽管关于二阶视觉的本质及其与一阶处理的关系存在一些争论,但现在有大量结果表明它们是分开处理的。然而,自然环境中存在的二阶结构的数量和性质尚不清楚。这是一个重要的问题,因为如果自然场景除了一阶信号外几乎不包含二阶结构,那么单独的二阶系统的概念将缺乏生态有效性。两种二阶视觉模型被应用于一些经过良好校准的自然图像。这两种模型都由一个定向空间滤波器的第一阶段、一个整流非线性以及随后的第二组滤波器组成。这两种模型在第一阶段和第二阶段滤波器之间的连接性方面有所不同。从模型中获取的输出图像表明自然图像确实包含有用的二阶结构。具体而言,这些模型揭示了纹理变化以及由此类变化定义的特征。高对比度区域(但不一定是高亮度区域)也被这些模型突出显示。模型所揭示的二阶结构与图像的一阶轮廓不相关,这表明这两种类型的图像“内容”在统计上可能是独立的。

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