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基于 Fibonacci 晶格的颜色量化与处理。

Color quantization and processing by Fibonacci lattices.

机构信息

IBM Thomas J. Watson Research Center, Hawthorne, NY 10532, USA.

出版信息

IEEE Trans Image Process. 2001;10(11):1712-25. doi: 10.1109/83.967399.

Abstract

Color quantization is sampling of three-dimensional (3-D) color spaces (such as RGB or Lab) which results in a discrete subset of colors known as a color codebook or palette. It is extensively used for display, transfer, and storage of natural images in Internet-based applications, computer graphics, and animation. We propose a sampling scheme which provides a uniform quantization of the Lab space. The idea is based on several results from number theory and phyllotaxy. The sampling algorithm is very much systematic and allows easy design of universal (image-independent) color codebooks for a given set of parameters. The codebook structure allows fast quantization and ordered dither of color images. The display quality of images quantized by the proposed color codebooks is comparable with that of image-dependent quantizers. Most importantly, the quantized images are more amenable to the type of processing used for grayscale ones. Methods for processing grayscale images cannot be simply extended to color images because they rely on the fact that each gray-level is described by a single number and the fact that a relation of full order can be easily established on the set of those numbers. Color spaces (such as RGB or Lab) are, on the other hand, 3-D. The proposed color quantization, i.e., color space sampling and numbering of sampled points, makes methods for processing grayscale images extendible to color images. We illustrate possible processing of color images by first introducing the basic average and difference operations and then implementing edge detection and compression of color quantized images.

摘要

颜色量化是对三维(3-D)颜色空间(如 RGB 或 Lab)进行采样,从而得到一个离散的颜色子集,称为颜色代码本或调色板。它广泛用于基于互联网的应用程序、计算机图形和动画中的自然图像的显示、传输和存储。我们提出了一种采样方案,该方案对 Lab 空间进行均匀量化。该想法基于数论和叶序学的几个结果。采样算法非常系统,可以为给定的参数集轻松设计通用(与图像无关)的颜色代码本。代码本结构允许对颜色图像进行快速量化和有序抖动。由所提出的颜色代码本量化的图像的显示质量可与图像相关的量化器相媲美。最重要的是,量化后的图像更适合用于灰度图像处理的类型。用于处理灰度图像的方法不能简单地扩展到彩色图像,因为它们依赖于每个灰度级由单个数字描述的事实,以及可以轻松在这些数字集上建立全序关系的事实。另一方面,颜色空间(如 RGB 或 Lab)是 3-D 的。所提出的颜色量化,即颜色空间采样和采样点的编号,使得用于处理灰度图像的方法可扩展到彩色图像。我们通过首先引入基本的平均值和差值操作,然后实现边缘检测和彩色量化图像的压缩,来说明对彩色图像进行处理的可能性。

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