彩色图像压缩利用色间相关

Larisa Goffman-Vinopal, M. Porat
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引用次数: 56

摘要

自然图像的RGB色彩成分之间具有高度相关性。大多数表示和压缩技术通过将原色转换为去相关的颜色空间(如YIQ或YUV)来减少颜色组件之间的冗余。本文提出了一种不同的色彩信息分析方法。由于颜色通道的高相关性隐含地暗示了组件之间的局部功能关系,因此可以通过将从属颜色近似为基础颜色的函数来用于替代框架。这样,编码颜色信息只需要减少数量的参数。给出了压缩结果,并与JPEG进行了比较,对影响编码质量的参数进行了研究和讨论。结果表明,与JPEG和相关应用中使用的YIQ/YUV去相关技术相比,基于相关的新方法具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Color image compression using inter-color correlation
Natural images are characterized by high correlation between their RGB color components. Most representation and compression techniques reduce the redundancies between color components by transforming the color primaries into a decorrelated color space, such as YIQ or YUV. In this paper a different approach to color information analysis is considered. Since the high correlation of color channels implicitly suggests a localized functional relation between the components, it could be used in an alternative framework by approximating subordinate colors as functions of a base color. This way, only a reduced number of parameters is required for coding the color information. Compression results are presented and compared with JPEG, and the parameters that affect the coding quality are studied and discussed. The results show the advantages of the new correlation-based approach over the YIQ/YUV decorrelation techniques as used in JPEG and related applications.
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