Image coding using optimized significance tree quantization

G. Davis, S. Chawla
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引用次数: 45

Abstract

A number of recent embedded transform coders, including Shapiro's (1993) EZW scheme, Said and Pearlman's (see IEEE Trans. Circuits and Systems for Video Technology, vol.6, no.3, p.243-250, 1996) SPIHT scheme, and Xiong et al. (see IEEE Signal Processing Letters, no.11, 1996) EZDCT scheme employ a common algorithm called significance tree quantization (STQ). Each of these coders have been selected from a large family of significance tree quantizers based on empirical work and a priori knowledge of the transform coefficient behavior. We describe an algorithm for selecting a particular form of STQ that is optimized for a given class of images. We apply our optimization procedure to the task of quantizing 8/spl times/8 DCT blocks. Our algorithm yields a fully embedded, low-complexity coder with performance from 0.7 to 2.5 dB better than baseline JPEG for standard test images.
图像编码采用优化的显著性树量化
最近的一些嵌入式转换编码器,包括Shapiro的(1993)EZW方案,Said和Pearlman的(参见IEEE Trans.)。视频技术电路与系统,第6卷,第6期。3, p.243-250, 1996) SPIHT方案,和熊等(见IEEE信号处理快报,第2期。11.1996) EZDCT方案采用一种称为显著性树量化(STQ)的通用算法。这些编码器中的每一个都是从基于经验工作和变换系数行为的先验知识的大量显著性树量化器中选择出来的。我们描述了一种算法,用于选择特定形式的STQ,该STQ针对给定的图像类进行了优化。我们将我们的优化程序应用于量化8/spl次/8 DCT块的任务。我们的算法产生了一个完全嵌入的、低复杂度的编码器,对于标准测试图像,其性能比基线JPEG好0.7到2.5 dB。
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