Rafegas Ivet, Vazquez-Corral Javier, Benavente Robert, Vanrell Maria, Alvarez Susana
J Opt Soc Am A Opt Image Sci Vis. 2017 May 1;34(5):827-837. doi: 10.1364/JOSAA.34.000827.
The extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to emphasize the fact that the number of channels is adapted to the image content. The higher the color complexity of an image, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding strategy using these color pivots as a basis. To evaluate the proposed approach, we measure the efficiency in an image categorization task. We show how a generic descriptor improves performance at the description level when applied to the MTT coding.
从彩色图像中提取空间色度特征通常是在每个颜色通道上独立进行的。常见的三维颜色空间，如RGB，对于自然图像呈现出较高的通道间相关性。使用颜色对立表示可以降低这种相关性，但在两个通用的红-绿和蓝-黄通道中，颜色差异较小的区域的空间结构并未得到充分捕捉。为了克服这些问题，我们提出了一种新的颜色编码方法，该方法适用于每幅图像的特定内容。我们的提议基于两个步骤：(a) 将通道数量设置为我们在每幅图像中找到的独特颜色的数量（避免通道相关性问题），以及(b) 构建一种通道表示，使每个颜色通道内的对比度差异最大化（避免局部对比度低的问题）。我们将这种方法称为多三色编码(MTT)，以强调通道数量适应图像内容这一事实。图像的颜色复杂度越高，可用于表示它的通道就越多。在这里，我们选择独特颜色作为图像中最主要的颜色，我们称之为颜色枢轴，并以这些颜色枢轴为基础构建新的颜色编码策略。为了评估所提出的方法，我们在图像分类任务中测量其效率。我们展示了一个通用描述符应用于MTT编码时如何在描述级别提高性能。
