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梯度感应和远距离亮度感应效应的多尺度滤波解释:对洛维年科(2003年)的回应

A multiscale filtering explanation of gradient induction and remote brightness induction effects: a reply to Logvinenko (2003).

作者信息

Blakeslee Barbara, McCourt Mark E

机构信息

Center for Visual Neuroscience, Department of Psychology, North Dakota State University, Fargo, ND 58105-5075, USA.

出版信息

Perception. 2005;34(7):793-802. doi: 10.1068/p5303x.

Abstract

Grating induction is a brightness effect in which a counterphase spatial brightness variation (a grating) is induced in a homogeneous test strip that is surrounded by an inducing luminance grating (McCourt, 1982 Vision Research 22 119-134). Moulden and Kingdom (1991 Vision Research 31 1999-2008) introduced an interesting variant of grating induction (sometimes referred to as gradient induction) in which multiple strips of either a linear luminance ramp or a sine-wave grating were interlaced with strips of homogeneous luminance. We (Blakeslee and McCourt, 1999 Vision Research 39 4361-4377) demonstrated that a simple multiscale filtering explanation could account for grating induction. Recently, however, Logvinenko (2003 Perception 32 621-626) presented several arguments impugning the adequacy of spatial filtering approaches to understanding brightness induction in gradient induction stimuli. We propose that Logvinenko's arguments apply only to a limited class of filtering models, specifically those which employ only a single spatial filter. To test this hypothesis we modeled gradient induction stimuli as a function of inducing contrast, as well as Logvinenko's (2003) remote induction stimulus, using our multiscale oriented difference-of-Gaussians (ODOG) model (Blakeslee and McCourt 1999). The ODOG model successfully predicts the appearance of the inducing strips and the homogeneous test strips in the gradient induction stimuli and the appearance of the test patches in the remote induction stimuli. These results refute Logvinenko's (2003) claims, and we interpret them as providing strong evidence for a multiscale filtering approach to understanding both gradient induction and remote brightness induction effects.

摘要

光栅诱导是一种亮度效应,即在由诱导亮度光栅包围的均匀测试条中诱导出反相空间亮度变化(光栅)(麦考特,1982年,《视觉研究》22卷,第119 - 134页)。莫尔登和金德姆(1991年,《视觉研究》31卷,第1999 - 2008页)引入了一种有趣的光栅诱导变体(有时称为梯度诱导),其中多条线性亮度斜坡或正弦波光栅条与均匀亮度条交错排列。我们(布莱克斯利和麦考特,1999年,《视觉研究》39卷,第4361 - 4377页)证明了一个简单的多尺度滤波解释可以解释光栅诱导。然而,最近,洛维年科(2003年,《感知》32卷,第621 - 626页)提出了几个论点,质疑空间滤波方法在理解梯度诱导刺激中的亮度诱导方面的充分性。我们认为洛维年科的论点仅适用于一类有限的滤波模型,具体来说,是那些仅使用单个空间滤波器的模型。为了检验这一假设,我们使用我们的多尺度定向高斯差分(ODOG)模型(布莱克斯利和麦考特,1999年),将梯度诱导刺激建模为诱导对比度的函数,以及洛维年科(2003年)的远程诱导刺激。ODOG模型成功地预测了梯度诱导刺激中诱导条和均匀测试条的外观,以及远程诱导刺激中测试斑块的外观。这些结果驳斥了洛维年科(2003年)的说法,我们将其解释为为理解梯度诱导和远程亮度诱导效应的多尺度滤波方法提供了有力证据。

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