Tolhurst D J, Tadmor Y
Physiological Laboratory, University of Cambridge, U.K.
Vision Res. 1997 Dec;37(23):3203-15. doi: 10.1016/s0042-6989(97)00119-3.
The psychophysical task of discriminating changes in the slopes of the amplitude spectra of complex images has been used in the past to test whether the human visual system might be optimised for coding the spatial structure in natural images (e.g. Knill et al., 1990; Tadmor & Tolhurst, 1994). We have reported that the dependency of these discrimination thresholds on the reference slope has the same overall general form, regardless of the particular digitised photographs that are used for generating the stimuli. The actual discrimination thresholds, however, differ markedly in magnitude for stimuli that are derived from different digitised photographs. Here, we describe a model that aims at explaining this diversity of threshold magnitudes: we suppose that the observer is detecting small changes in image contrast estimated within limited spatial-frequency bands of about 1 octave bandwidth. This local-contrast analysis reveals that contrast changes in only one frequency band are of comparable magnitudes to the changes that observers need for detecting differences in the Michelson contrast of simple sinusoidal gratings. The success of this band-limited contrast model is further shown in experiments where the slopes of the amplitude spectra of stimuli were changed only within restricted frequency bands. We show that when the slope is changed outside the limited frequency band implicated by the contrast model, the observer's thresholds are greatly elevated. Thresholds remain unchanged when slope changes are made within the implicated band. We also find that the exact bandwidth of the contrast operator is not critical, provided that it is in the range of about 0.6-1.5, which is the characteristic bandwidth range of V1 neurons.
过去曾使用辨别复杂图像幅度谱斜率变化的心理物理学任务来测试人类视觉系统是否可能针对自然图像中的空间结构编码进行了优化（例如，Knill等人，1990年；Tadmor和Tolhurst，1994年）。我们已经报道，无论用于生成刺激的具体数字化照片如何，这些辨别阈值对参考斜率的依赖性具有相同的总体一般形式。然而，对于源自不同数字化照片的刺激，实际的辨别阈值在大小上有显著差异。在这里，我们描述了一个旨在解释这种阈值大小多样性的模型：我们假设观察者正在检测在大约1倍频程带宽的有限空间频率带内估计的图像对比度的微小变化。这种局部对比度分析表明，只有一个频带中的对比度变化与观察者检测简单正弦光栅的迈克尔逊对比度差异所需的变化幅度相当。在刺激的幅度谱斜率仅在受限频带内变化的实验中，进一步证明了这种带限对比度模型的成功。我们表明，当斜率在对比度模型所涉及的有限频带之外变化时，观察者的阈值会大大提高。当在涉及的频带内进行斜率变化时，阈值保持不变。我们还发现，对比度算子的确切带宽并不关键，只要它在大约0.6 - 1.5的范围内，这是V1神经元的特征带宽范围。
