Maddess T, Nagai Y, James A C, Ankiewcz A
Centre for Visual Sciences, Research School of Biological Sciences, Australian National University, Canberra, ACT 0200, Australia.
Vision Res. 2004 May;44(11):1093-113. doi: 10.1016/j.visres.2003.12.012.
A quantitative method is presented for creating a large number of classes of binary (256) and ternary (7.62 x 10(12)) textures. The binary textures are presented as black and white (contrasts -1 and 1). The ternary textures have three levels: black, white and the mean luminance gray (contrasts -1, 0 and 1). The ternary patterns in particular display a wide variety of properties, including depth cues from disparity and lighting. Given the very large number of ternary patterns, we present guidelines and analytical methods for selecting sets of textures with particular image qualities and/or nonlinear relationships between pixels. The second- and third-order correlation functions of several thousand examples were examined to reveal patterns that are functionally isotrigon with other textures and or with uniformly distributed noise patterns.
本文提出了一种定量方法,用于创建大量的二元(256种)和三元(7.62×10¹²种)纹理类别。二元纹理呈现为黑色和白色(对比度为-1和1)。三元纹理有三个级别:黑色、白色和平均亮度灰色(对比度为-1、0和1)。特别是三元图案展现出各种各样的特性,包括视差和光照产生的深度线索。鉴于三元图案数量众多,我们提出了指导方针和分析方法,用于选择具有特定图像质量和/或像素间非线性关系的纹理集。我们检查了数千个示例的二阶和三阶相关函数,以揭示与其他纹理和/或均匀分布噪声图案在功能上呈等三角关系的图案。