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一种用于人类模式识别中空间整合的窗口模型。

A window model for spatial integration in human pattern discrimination.

作者信息

Näsänen R E, Kukkonen H T, Rovamo J M

机构信息

Department of Physiology, University of Helsinki, Finland.

出版信息

Invest Ophthalmol Vis Sci. 1995 Aug;36(9):1855-62.

PMID:7635659
Abstract

PURPOSE

A simple model of human visual pattern discrimination was designed and tested experimentally. The model is based on two assumptions. First, at any glimpse the spatial integration of image information is limited to a window. Second, the observer generates a tailored discriminator for the signals in question using available information. The model is composed of a spatial integration window followed by an ideal discriminator.

METHODS

The model was tested by comparing its performance with that of human observers in orientation and contrast discrimination. Using a two-alternative, forced-choice method, human orientation and contrast discrimination thresholds were measured for cosine gratings of various areas and spatial frequencies in the presence of two-dimensional spatial noise.

RESULTS

Orientation discrimination thresholds decreased considerably with increasing grating area. Thus, there was clear spatial integration. However, in contrast discrimination, thresholds appeared to decrease only slightly. To make the two tasks comparable, the results also were expressed in terms of efficiency. Human efficiency decreased with grating area in a similar way in the two tasks. This suggests that the factors limiting spatial integration are the same in both tasks. Indeed, the threshold data were explained by the model with the same window size in both tasks with good accuracy. The absolute performance of the model was approximately equal to that of human observers.

CONCLUSIONS

The success of the model supports the hypothesis of a spatial integration window. It also supports the idea that human observers use knowledge about the signals to generate an efficient discriminator.

摘要

目的

设计并通过实验测试了一种简单的人类视觉模式辨别模型。该模型基于两个假设。第一,在任何一瞥中,图像信息的空间整合都局限于一个窗口。第二,观察者利用可用信息为相关信号生成一个定制的辨别器。该模型由一个空间整合窗口和一个理想辨别器组成。

方法

通过将该模型在方向和对比度辨别方面的性能与人类观察者的性能进行比较来测试该模型。使用二选一的强制选择方法,在存在二维空间噪声的情况下,测量了人类对各种面积和空间频率的余弦光栅的方向和对比度辨别阈值。

结果

方向辨别阈值随着光栅面积的增加而显著降低。因此,存在明显的空间整合。然而,在对比度辨别中,阈值似乎仅略有下降。为了使这两项任务具有可比性,结果也以效率的形式表示。在这两项任务中,人类效率随着光栅面积的增加以类似的方式降低。这表明限制空间整合的因素在这两项任务中是相同的。实际上,该模型用相同的窗口大小在两项任务中都能很好地解释阈值数据。该模型的绝对性能与人类观察者的性能大致相当。

结论

该模型的成功支持了空间整合窗口的假设。它还支持人类观察者利用关于信号的知识来生成高效辨别器的观点。

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