Burgess A E, Li X, Abbey C K
Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
J Opt Soc Am A Opt Image Sci Vis. 1997 Sep;14(9):2420-42. doi: 10.1364/josaa.14.002420.
We measured human observers' detectability of aperiodic signals in noise with two components (white and low-pass Gaussian). The white-noise component ensured that the signal detection task was always noise limited rather than contrast limited (i.e., image noise was always much larger than observer internal noise). The low-pass component can be considered to be a statistically defined background. Contrast threshold elevation was not linearly related to the rms background contrast. Our results gave power-law exponents near 0.6, similar to that found for deterministic masking. The Fisher-Hotelling linear discriminant model assessed by Rolland and Barrett [J. Opt. Soc. Am. A 9, 649 (1992)] and the modified nonprewhitening matched filter model suggested by Burgess [J. Opt. Soc. Am. A 11, 1237 (1994)] for describing signal detection in statistically defined backgrounds did not fit our more precise data. We show that it is not possible to find any nonprewhitening model that can fit our data. We investigated modified Fisher-Hotelling models by using spatial-frequency channels, as suggested by Myers and Barrett [J. Opt. Soc. Am. A 4, 2447 (1987)]. Two of these models did give good fits to our data, which suggests that we may be able to do partial prewhitening of image noise.
我们测量了人类观察者对具有两个分量(白噪声和低通高斯噪声)的噪声中非周期性信号的可检测性。白噪声分量确保信号检测任务始终受噪声限制而非对比度限制(即图像噪声始终远大于观察者内部噪声)。低通分量可被视为统计定义的背景。对比度阈值升高与均方根背景对比度并非线性相关。我们的结果给出的幂律指数接近0.6,与确定性掩蔽的情况类似。罗兰和巴雷特[《美国光学学会杂志A》9, 649 (1992)]评估的费希尔 - 霍特林线性判别模型以及伯吉斯[《美国光学学会杂志A》11, 1237 (1994)]提出的用于描述统计定义背景中信号检测的改进非白化匹配滤波器模型均不能拟合我们更精确的数据。我们表明,找不到任何能拟合我们数据的非白化模型。我们按照迈尔斯和巴雷特[《美国光学学会杂志A》4, 2447 (1987)]的建议,通过使用空间频率通道研究了改进的费希尔 - 霍特林模型。其中两个模型确实能很好地拟合我们的数据,这表明我们或许能够对图像噪声进行部分白化处理。