Karhunen-Loeve变换在自然彩色图像分析中的应用

R. Kouassi, J. Devaux, Pierre Gouton, Michel Paindavoine
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引用次数: 22

摘要

目前的图像捕获系统基于红、绿、蓝(R、G、B)原则。但是,这种捕捉彩色图像的模型不同于人类的视觉系统。因此,为了获得接近人类系统的表示,可以使用强度和色度空间。由于这种表示是非线性的,它引入了颜色不稳定性。因此,为了分析自然彩色图像,我们使用Karhunen-Loeve空间,它允许对颜色成分进行大的去相关,对非常均匀的图像进行高清晰度的颜色和增加的压缩比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of the Karhunen-Loeve transform for natural color images analysis
The current systems of image capture are based on red, green and blue (R,G,B) principles. But, this model of capturing color images is different from the human visual system. So, to obtain a representation which approaches the human system, one uses the intensity and chrominance space. As this representation is non-linear, it introduces color instability. Thus, to analyze natural color images, we use the Karhunen-Loeve space, which allows a large decorrelation of the color components, a high definition of colors and an increased compression ratio for very homogeneous images.
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