Eckstein M P, Ahumada A J, Watson A B
NASA Ames Research Center, Cedars-Sinai Medical Center, Los Angeles, California 90048-1865, USA.
J Opt Soc Am A Opt Image Sci Vis. 1997 Sep;14(9):2406-19. doi: 10.1364/josaa.14.002406.
Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.
对叠加在两个相同背景之一上的信号进行视觉检测的研究表明,当背景具有高对比度且在空间频率和/或方向上与信号相似时,检测性能会下降。为了解释这一发现,模型包括一种对比度增益控制机制,该机制在空间频率、方向和空间上汇总活动,以抑制(除法方式)对信号敏感的感受器的反应。在观察者必须检测由于添加视觉噪声而添加到M个不同背景之一中的已知信号的任务中,性能下降的主要来源是图像中的随机噪声和次优视觉处理。我们研究了这两种性能下降源(对比度增益控制和背景变化)在信号嵌入复杂空间变化背景(结构化背景)中M个位置之一的任务中是如何相互作用的。我们使用从患者数字医学图像中提取的背景。为了将固定确定性背景(对比度增益控制)的影响与背景变化的影响隔离开来,我们在三种不同的背景条件下进行检测实验:(1)均匀背景,(2)结构化背景的重复样本,以及(3)结构化背景的不同样本。结果表明,人类视觉检测从均匀背景条件到重复背景条件会下降,在不同背景条件下甚至会进一步下降。这些结果表明,对比度增益控制机制和背景随机变化都会降低人类在复杂空间变化背景中检测信号的性能。使用滤波器模型和添加的白噪声来生成采样效率、等效内部噪声、等效对比度增益控制引起的噪声以及由于结构化背景变化引起的等效噪声的估计值。