AVQ算法:水印和压缩性能

Raffaele Pizzolante, B. Carpentieri, Aniello Castiglione, G. Maio
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引用次数: 24

摘要

本文综述了Constantinescu和Storer提出的用于有损图像压缩的自适应矢量量化算法。AVQ结合了基于字典的算法单次处理输入的潜力和矢量量化的潜力来近似数据。我们讨论了一个开源实现,并报告了使用不同大小的字典实现的结果。在此基础上,重点讨论了数字水印技术在多媒体内容中的版权保护问题。此外,我们还描述了一种可以提高数字不可见水印鲁棒性的方法。该方法包括在压缩过程中将水印扩散到图像中。我们假设压缩算法知道水印的位置:当算法识别出包含水印的块时,该块以无损失模式编码并分布在整个图像中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The AVQ Algorithm: Watermarking and Compression Performances
In this paper we review the Adaptive Vector Quantization algorithm for lossy image compression, introduced by Constantinescu and Storer. AVQ combines the potentiality of a dictionary-based algorithm to process input in single-pass with the potentiality of Vector Quantization to approximate data. We discuss an open-source implementation and report the achieved results by this implementation with different size of the dictionary. Subsequently, we consider the problem of the copyright protection in multimedia contents, by focusing our attention on the Digital Watermarking. In addition we describe an approach for this algorithm that permits to improve the robustness of digital invisible watermarks. The proposed approach consists of spreading the watermark into the image during the compression process. We assume that the compression algorithm is aware of the positions of the watermarks: when the algorithm identifies the block containing the watermark, then this block is encoded in loss less mode and is spread all over the image.
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