基于小波图像编码的有限状态点阵矢量量化

J. Ni, K. Ho, K. Tse
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引用次数: 0

摘要

众所周知,真实图像的各个子带之间存在很强的能量相关性。引入了一种新的强大的有限状态矢量量化技术(FSVQ),以充分利用图像在不同尺度上的小波域自相似性。R/sup / N/中的晶格具有相当大的结构,因此,Lattice VQ提供了设计简单和减少编码复杂性的承诺。FSVQ和LVQ的结合产生了所谓的FSLVQ,它被证明是成功地利用了跨尺度的能量相关性,并且实现起来足够简单。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Finite state lattice vector quantization for wavelet-based image coding
It is well known that there exists strong energy correlation between various subbands of a real-world image. A new powerful technique of Finite State Vector Quantization (FSVQ) has been introduced to fully exploit the self-similarity of the image in wavelet domain across different scales. Lattices in R/sup N/ have considerable structure, and hence, Lattice VQ offers the promise of design simplicity and reduced complexity encoding. The combination of FSVQ and LVQ gives rise to the so-called FSLVQ, which is proved to be successful in exploiting the energy correlation across scales and is simple enough in implementation.
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