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幅度谱统计对自然图像变化的中央凹和周边辨别力的影响以及一种多分辨率模型。

The effects of amplitude-spectrum statistics on foveal and peripheral discrimination of changes in natural images, and a multi-resolution model.

作者信息

Párraga C A, Troscianko T, Tolhurst D J

机构信息

Department of Experimental Psychology, University of Bristol, 8 Woodland Road, Bristol, BS8 1TN, UK.

出版信息

Vision Res. 2005 Nov;45(25-26):3145-68. doi: 10.1016/j.visres.2005.08.006. Epub 2005 Sep 22.

Abstract

Psychophysical thresholds were measured for discriminating small changes in spatial features of naturalistic scenes (morph sequences), for foveal and peripheral vision, and under M-scaling. Sensitivity was greatest for scenes with near natural Fourier amplitude slope, perhaps implying that human vision is optimised for natural scene statistics. A low-level model calculated differences in local contrast between pairs of images within a few spatial frequency channels with bandwidth like neurons in V1. The model was "customised" to each observer's contrast sensitivity function for sinusoidal gratings, and it could replicate the "U-shaped" relationships between discrimination threshold and spectral slope, and many differences between picture sets and observers. A single-channel model and an ideal-observer analysis both failed to capture the U-shape.

摘要

测量了心理物理学阈值,以区分自然场景(形态序列)空间特征的微小变化,测量条件为中央凹和周边视觉以及M标度。对于具有接近自然傅里叶振幅斜率的场景,敏感度最高,这可能意味着人类视觉针对自然场景统计进行了优化。一个低层次模型计算了在几个空间频率通道内成对图像之间的局部对比度差异,这些通道的带宽类似于V1区神经元。该模型针对每个观察者对正弦光栅的对比度敏感度函数进行了“定制”,并且能够复制辨别阈值与光谱斜率之间的“U形”关系,以及图片集和观察者之间的许多差异。单通道模型和理想观察者分析均未能捕捉到这种U形关系。

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