一种基于局部自适应编码的图像压缩新方案

Chinchen Chang, Yung-Chen Chou, Chia-Chen Lin
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引用次数: 0

摘要

矢量量化(VQ)是一种简单而广泛应用的压缩技术。对于图像压缩,VQ既提供固定的压缩比,又保持可接受的失真。但是,VQ的性能在压缩图像的图像质量和用于编码和解码的码本大小方面仍然可以得到改进。本文提出了一种新的类VQ图像压缩方法,利用局部自适应编码的概念来提高传统VQ的压缩性能。实验结果表明,该方法压缩后的图像质量平均高于30 dB,码本中使用的码字数少于传统的VQ方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Image Compression Scheme Based on Locally Adaptive Coding
Vector quantization (VQ) is a simple and widely used compression technology in many applications. For image compression, VQ provides both a fixed compression ratio and maintains acceptable distortion. However, the performance of VQ still can be improved in terms of the image quality of compressed images and codebook size used for encoding and decoding. In this paper, a new VQ-like image compression method is proposed to improve the performance of traditional VQ by using locally adaptive coding concept. The experimental results confirm that the image quality of the compressed image offered by the proposed method is higher than 30 dB on average, and the number of codewords used in our codebook is less than that required by traditional VQ.
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