Rovamo J, Ukkonen O, Thompson C, Näsänen R
Department of Vision Sciences, University of Aston, Birmingham, United Kingdom.
Invest Ophthalmol Vis Sci. 1994 Apr;35(5):2611-9.
The human foveal visual system in a detection task was recently modeled as a simple image processor comprising low-pass filtering due to the optical modulation transfer function of the eye, high-pass filtering (lateral inhibition) due to the neural modulation transfer function of visual pathways, addition of internal neural noise, and detection by a local matched filter, the efficiency of which decreases with increasing grating area. The applicability of this model was now tested by studying spatial integration for sums of various numbers of cosine gratings with different orientations.
Binocular root-mean-square contrast sensitivity was measured as a function of area for sums of cosine gratings (n = 1 to 16) with the same contrast, phase, and spatial frequency but with an orientation difference of 180/n between the components.
In agreement with the model, contrast sensitivity increased in proportion to the square root of grating area at small areas. When grating area exceeded its critical value, the increase saturated, and contrast sensitivity then became independent of area. The critical area and maximum contrast sensitivity of spatial integration first decreased with an increasing number of components, reaching minima at n = 5 to 6, but increased thereafter. A plausible explanation for the variation of critical area and maximum sensitivity could be the variation of the amount of contour and detail per unit area in the sums of cosine gratings. Critical area divided by maximum sensitivity squared refers to the contrast energy threshold at small grating areas. It was independent of the number of components but, because of lateral inhibition, decreased in inverse proportion to spatial frequency squared. Contrast energy threshold as a function of normalized grating area (grating area divided by critical area) also was independent of the number of components and decreased in inverse proportion to spatial frequency squared.
Within the framework of the local matched filter model, the dependency of contrast sensitivity on the grating area and number of orientation components resulted from the decrease in the efficiency of contrast energy collection, which was probably due to the increasing amount of contour and detail in the stimulus to be detected.
人类中央凹视觉系统在检测任务中最近被建模为一个简单的图像处理器,包括由于眼睛的光学调制传递函数引起的低通滤波、由于视觉通路的神经调制传递函数引起的高通滤波(侧向抑制)、内部神经噪声的添加以及由局部匹配滤波器进行检测,该滤波器的效率随着光栅面积的增加而降低。现在通过研究不同数量、不同方向的余弦光栅总和的空间整合来测试该模型的适用性。
测量双眼均方根对比度敏感度,其作为具有相同对比度、相位和空间频率但各分量之间取向差为180/n的余弦光栅总和(n = 1至16)的面积的函数。
与模型一致,在小面积时,对比度敏感度与光栅面积的平方根成比例增加。当光栅面积超过其临界值时,增加趋于饱和,然后对比度敏感度变得与面积无关。空间整合的临界面积和最大对比度敏感度首先随着分量数量的增加而降低,在n = 5至6时达到最小值,但此后增加。临界面积和最大敏感度变化的一个合理原因可能是余弦光栅总和中每单位面积的轮廓和细节量的变化。临界面积除以最大敏感度的平方指的是小光栅面积时的对比度能量阈值。它与分量数量无关,但由于侧向抑制,与空间频率平方成反比降低。对比度能量阈值作为归一化光栅面积(光栅面积除以临界面积)的函数也与分量数量无关,并且与空间频率平方成反比降低。
在局部匹配滤波器模型的框架内,对比度敏感度对光栅面积和取向分量数量的依赖性源于对比度能量收集效率的降低,这可能是由于待检测刺激中轮廓和细节量的增加。