Harmon L D, Julesz B
Science. 1973 Jun 15;180(4091):1194-7. doi: 10.1126/science.180.4091.1194.
It is difficult to recognize portraits that have been coarsely sampled and quantized. Blurring such images improves recognition. A simple, straightforward explanation is that high-frequency noise introduced by the sampling and quantizing must be removed by low-pass filtering to improve the signal-to-noise ratio and hence signal detectability or recognition. Experiments reported here, suggested on the basis of a different model, show instead that noise bands that are spectrally adjacent to the picture's spectrum are considerably more effective in suppressing recognition.
识别经过粗略采样和量化的肖像很困难。对这类图像进行模糊处理可提高识别率。一个简单直接的解释是，采样和量化引入的高频噪声必须通过低通滤波来去除，以提高信噪比，从而提高信号的可检测性或识别率。基于不同模型提出的此处所报告的实验却表明，在频谱上与图像频谱相邻的噪声带在抑制识别方面要有效得多。
