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相位噪声与自然图像分类

Phase noise and the classification of natural images.

作者信息

Wichmann Felix A, Braun Doris I, Gegenfurtner Karl R

机构信息

Max-Planck-Institut für biologische Kybernetik, Spemannstr. 38, 72076 Tübingen, Germany.

出版信息

Vision Res. 2006 Apr;46(8-9):1520-9. doi: 10.1016/j.visres.2005.11.008. Epub 2005 Dec 27.

DOI:10.1016/j.visres.2005.11.008
PMID:16384589
Abstract

We measured the effect of global phase manipulations on a rapid animal categorization task. The Fourier spectra of our images of natural scenes were manipulated by adding zero-mean random phase noise at all spatial frequencies. The phase noise was the independent variable, uniformly and symmetrically distributed between 0 degrees and +/-180 degrees . Subjects were remarkably resistant to phase noise. Even with +/-120 degrees phase noise subjects were still performing at 75% correct. The high resistance of the subjects' animal categorization rate to phase noise suggests that the visual system is highly robust to such random image changes. The proportion of correct answers closely followed the correlation between original and the phase noise-distorted images. Animal detection rate was higher when the same task was performed with contrast reduced versions of the same natural images, at contrasts where the contrast reduction mimicked that resulting from our phase randomization. Since the subjects' categorization rate was better in the contrast experiment, reduction of local contrast alone cannot explain the performance in the phase noise experiment. This result obtained with natural images differs from those obtained for simple sinusoidal stimuli were performance changes due to phase changes are attributed to local contrast changes only. Thus the global phase-change accompanying disruption of image structure such as edges and object boundaries at different spatial scales reduces object classification over and above the performance deficit resulting from reducing contrast. Additional color information improves the categorization performance by 2%.

摘要

我们测量了全局相位操纵对快速动物分类任务的影响。通过在所有空间频率上添加零均值随机相位噪声,对我们的自然场景图像的傅里叶频谱进行了操纵。相位噪声是自变量,在0度和+/-180度之间均匀且对称地分布。受试者对相位噪声具有显著的抗性。即使存在+/-120度的相位噪声,受试者的正确率仍能达到75%。受试者的动物分类率对相位噪声的高抗性表明视觉系统对这种随机图像变化具有高度的鲁棒性。正确答案的比例紧密跟随原始图像与相位噪声失真图像之间的相关性。当使用相同自然图像的对比度降低版本执行相同任务时,动物检测率更高,此时对比度降低模拟了我们相位随机化所导致的情况。由于在对比度实验中受试者的分类率更高,仅局部对比度的降低无法解释相位噪声实验中的表现。用自然图像获得的这一结果与用简单正弦刺激获得的结果不同,在简单正弦刺激实验中,由于相位变化导致的性能变化仅归因于局部对比度变化。因此,在不同空间尺度上伴随图像结构(如图像边缘和物体边界)破坏的全局相位变化,除了对比度降低导致的性能缺陷之外,还会降低物体分类。额外的颜色信息使分类性能提高了2%。

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