McIlhagga William
Bradford School of Optometry and Vision Science, University of Bradford, Richmond Road, Bradford BD7 1DP, England, United Kingdom.
Vision Res. 2018 Dec;153:30-36. doi: 10.1016/j.visres.2018.09.007. Epub 2018 Oct 10.
Edge detection is widely believed to be an important early stage in human visual processing. However, there have been relatively few attempts to map human edge detection filters. In this study, observers had to locate a randomly placed step edge in brown noise (the integral of white noise) with a 1/f power spectrum. Their responses were modelled by assuming the probability the observer chose an edge location depended on the response of their own edge detection filter to that location. The observer's edge detection filter was then estimated by maximum likelihood methods. The filters obtained were odd-symmetric and similar to a derivative of Gaussian, with a peak-to-trough width of 0.1-0.15 degrees. These filters are compared with previous estimates of edge detectors in humans, and with neurophysiological receptive fields and theoretical edge detectors.
边缘检测被广泛认为是人类视觉处理中的一个重要早期阶段。然而，绘制人类边缘检测滤波器的尝试相对较少。在本研究中，观察者必须在具有1/f功率谱的棕色噪声（白噪声的积分）中定位随机放置的阶跃边缘。通过假设观察者选择边缘位置的概率取决于其自身边缘检测滤波器对该位置的响应，对他们的反应进行建模。然后通过最大似然方法估计观察者 的边缘检测滤波器。获得的滤波器是奇对称的，类似于高斯导数，峰谷宽度为0.1-0.15度。将这些滤波器与先前对人类边缘检测器的估计、神经生理感受野和理论边缘检测器进行了比较。
