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Justus-Liebig University Giessen, 35394 Giessen, Germany

机译:Justus-Liebig大学Giessen,35394 Giessen,德国

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摘要

Recent physiological evidence has shown that neurons at the early visual stages are selective for a combination of color, luminance and orientation. Neurons with a linear response tuning, resulting in broad tuning curves, are found at all stages, but the proportion of nonlinear neurons, narrowly tuned for color, increases along the visual pathway. We ran psychophysical experiments to characterize the number and tuning widths of the mechanisms underlying image segmentation. We used a noise masking paradigm with different types of noise to disentangle mechanisms with narrow and broad tuning characteristics. The data were best described by a chromatic detection model with multiple, broadly tuned mechanisms, where narrow tuning curves emerge due to off-axis looking. We then analyzed a set of calibrated natural images and determined the joint statistics of color and luminance edges. The majority of edges in natural scenes was characterized by a contrast in both color and luminance, while some prominent object boundaries were signalled only in the chromatic plane. Based on the converging evidence from different disciplines we conclude that multiple linear, broadly tuned mechanisms which are selective for a combination of chromatic contrast, luminance contrasts and orientations play a central role for contour extraction and robust image segmentation.
机译:最近的生理证据表明,早期视级的神经元是针对颜色,亮度和方向的组合选择性。在所有阶段发现具有线性响应调谐的神经元,导致广泛的调谐曲线,但是非线性神经元的比例狭窄地调整颜色,沿着视觉途径增加。我们跑了精神物理实验,以表征底层图像分割机制的数量和调谐宽度。我们使用具有不同类型的噪声的噪声掩蔽范例来解散机制,具有狭窄和广泛的调整特性。该数据最好由具有多个宽泛调整机制的色度检测模型来描述,其中窄调曲线由于轴外观察而出现。然后,我们分析了一组校准的自然图像,并确定了颜色和亮度边缘的关节统计。自然场景中的大多数边缘的特征在于颜色和亮度的对比度,而仅在彩色平面中发出一些突出的对象边界。基于来自不同学科的融合证据我们得出结论,用于组合色度对比度,亮度对比度和取向的组合选择性的多个线性广泛调节机制在轮廓提取和鲁棒图像分割中起着核心作用。

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