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Toward a Full Probability Model of Edges in Natural Images

机译:朝着自然图像边缘的完整概率模型

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We investigate the statistics of local geometric structures in natural images. Previous studies [13,14] of high-contrast 3 * 3 natural image patches have shown that, in the state space of these patches, we have a concentration of data points along a low-dimensional non-linear manifold that corresponds to edge structures. In this paper we extend our analysis to a filter-based multiscale image representation, namely the local 3-jet of Gaussian scale-space representations. A new picture of natural image statistics seems to emerge, where primitives (such as edges, blobs, and bars) generate low-dimensional non-linear structures in the state space of image data.
机译:我们调查自然图像中局部几何结构的统计数据。以前的研究[13,14]的高对比度3 * 3自然图像贴片已经表明,在这些贴片的状态空间中,我们具有沿着对应于边缘结构的低维非线性歧管的数据点浓度。在本文中,我们将分析扩展到基于滤波器的多尺度图像表示,即高斯级尺度空间表示的本地3射流。自然图像统计的新图片似乎是出现的,其中基元(如边缘,斑点和条形)在图像数据的状态空间中产生低维非线性结构。

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