Victor J D, Conte M M
Department of Neurology and Neuroscience, Cornell University Medical College, New York, NY 10021, USA.
Vision Res. 1996 Jun;36(11):1615-31. doi: 10.1016/0042-6989(95)00219-7.
Isodipole textures are pairs of texture ensembles whose autocorrelations, and hence power spectra, are equal. Examples of readily discriminable isodipole textures are well known. Such discriminations appear to require feature extraction, since the isodipole condition eliminates ensemble differences in spatial frequency content. We studied the effects of phase decorrelation on VEP indices of discrimination of isodipole texture pairs. Phase decorrelation, which ranged from 0.125 pi radians (slight randomization) to pi radians (complete randomization), was introduced in two ways: by independent jittering of each spatial Fourier component, and by a product method, which preserved correlations among certain quadruples of spatial Fourier components, despite pairwise decorrelation. For the even/random isodipole texture pair, independent phase decorrelation greater than 0.5 pi radians markedly reduced VEP indices of texture discrimination for all check sizes, and eliminated them entirely for check sizes of 8 min or greater. However, the product method preserved texture discrimination signals even with complete pairwise randomization of spatial phases. For the triangle/random isodipole texture pair, both kinds of phase decorrelation eliminated VEP indices of texture discrimination. These results imply that isodipole texture discrimination is based on fundamentally local processing, and not on global Fourier amplitudes-since the phase manipulations which eliminate texture discrimination preserve the Fourier amplitudes. The dependence of the antisymmetric response component (the odd harmonics) on phase decorrelation and texture type is consistent with a previously proposed model for feature extraction, and leads to constraints on how texture processing is modulated by contrast. The limited contribution of global spectral characteristics for small checks is consistent with a previously identified breakdown in scale-invariant processing.
等偶极纹理是纹理集合对,其自相关以及功率谱相等。易于区分的等偶极纹理的例子是众所周知的。由于等偶极条件消除了空间频率内容中的集合差异,这种区分似乎需要特征提取。我们研究了相位去相关对等偶极纹理对辨别VEP指标的影响。相位去相关范围从0.125π弧度(轻微随机化)到π弧度(完全随机化),通过两种方式引入:通过每个空间傅里叶分量的独立抖动,以及通过乘积方法,该方法保留了某些空间傅里叶分量四元组之间的相关性,尽管是成对去相关。对于偶数/随机等偶极纹理对,大于0.5π弧度的独立相位去相关显著降低了所有检查尺寸下纹理辨别的VEP指标,对于8分钟或更大的检查尺寸则完全消除了这些指标。然而,即使空间相位完全成对随机化,乘积方法仍保留了纹理辨别信号。对于三角形/随机等偶极纹理对,两种相位去相关都消除了纹理辨别的VEP指标。这些结果意味着等偶极纹理辨别基于根本上的局部处理,而不是基于全局傅里叶幅度——因为消除纹理辨别的相位操作保留了傅里叶幅度。反对称响应分量(奇次谐波)对相位去相关和纹理类型的依赖性与先前提出的特征提取模型一致,并导致了关于对比度如何调制纹理处理的限制。小检查中全局光谱特征的有限贡献与先前确定的尺度不变处理中的故障一致。