Luntinen O, Rovamo J, Näsänen R
Department of Vision Sciences, Aston University, Birmingham, England.
Vision Res. 1995 Aug;35(16):2339-46. doi: 10.1016/0042-6989(94)00309-a.
We extended the contrast detection model of human vision to temporal integration by taking into account the effect of exposure duration on contrast sensitivity for stationary gratings. The extended model thus comprised: (i) low-pass filtering due to the optical modulation transfer function of the eye; (ii) high-pass filtering (lateral inhibition) due to the neural modulation transfer function of the visual pathways; (iii) addition of internal neural noise; and (iv) detection by a local matched filter whose efficiency for gratings decreased with increasing area and exposure duration. To test the model we measured binocular contrast sensitivity in foveal photopic vision as a function of exposure duration and area for sinusoidal gratings with equiluminous surround at spatial frequencies of 0.25-16 c/deg. In agreement with the model, contrast sensitivity at all grating areas first increased in proportion to square root of t when exposure duration (t) was shorter than critical duration. Thereafter the increase saturated and contrast sensitivity became independent of exposure time. Critical exposure duration was found to be independent of grating area but increased with spatial frequency. Similarly, at all exposure durations contrast sensitivity first increased in proportion to square root of A when grating area (A) was smaller than critical area. Thereafter the increase saturated and contrast sensitivity became independent of area. Critical area was found to be independent of exposure duration but decreased with increasing spatial frequency. The extended model explained 95-97% of the total variance of our contrast sensitivity data at the spatial frequencies studied. Our results also mean that spatial and temporal integration processes are mutually independent and thus area and time are separable variables in the detection of stationary gratings.
我们通过考虑曝光持续时间对静止光栅对比度敏感度的影响，将人类视觉的对比度检测模型扩展到时间整合。扩展后的模型包括：(i) 由于眼睛的光学调制传递函数产生的低通滤波；(ii) 由于视觉通路的神经调制传递函数产生的高通滤波（侧向抑制）；(iii) 添加内部神经噪声；以及 (iv) 由局部匹配滤波器进行检测，该滤波器对光栅的效率随面积和曝光持续时间的增加而降低。为了测试该模型，我们测量了中央凹明视觉中双眼对比度敏感度，作为曝光持续时间和面积的函数，针对空间频率为0.25 - 16 c/deg且具有等亮度背景的正弦光栅。与模型一致，当曝光持续时间（t）短于临界持续时间时，所有光栅面积下的对比度敏感度首先与t的平方根成正比增加。此后，增加趋于饱和，对比度敏感度变得与曝光时间无关。发现临界曝光持续时间与光栅面积无关，但随空间频率增加。同样，在所有曝光持续时间下，当光栅面积（A）小于临界面积时，对比度敏感度首先与A的平方根成正比增加。此后，增加趋于饱和，对比度敏感度变得与面积无关。发现临界面积与曝光持续时间无关，但随空间频率增加而减小。扩展后的模型解释了我们在所研究空间频率下对比度敏感度数据总方差的95 - 97%。我们的结果还意味着空间和时间整合过程相互独立，因此在检测静止光栅时，面积和时间是可分离的变量。
