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A DWT-DCT image compression scheme.

机译:DWT-DCT图像压缩方案。

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摘要

The heavy growth of multimedia based web applications has increased the need for efficient coding of signals and images and has made compression of such signals central to storage and communication technology. The block based Discrete Cosine Transform (DCT) has been the building block of most image compression algorithms and has been adopted in the earlier JPEG standard and in the MPEG series video standards. Over the last decade, research activities in image coding have centered largely around the Discrete Wavelet Transform (DWT) which provides an elegant representation suitable for compression and as such it has been included in the latest JPEG-2000 standard. With proper re-ordering of the DCT coefficients, efficient quantization schemes developed in the context of wavelet compression can be applied in the DCT domain. The objective of this thesis is to combine the better features of both the transformations and develop a hybrid image coding algorithm with low computational complexity. An image is decomposed using a one-level DWT and then a block based DCT is applied to the low-pass subband. The quantization scheme adopted is the Difference Reduction algorithm (DR) to obtain an embedded, progressive image compression scheme. The scheme performs better than the DCT based coders and shows good subjective performance over a wide range of compression ratios.
机译:基于多媒体的Web应用程序的迅猛发展增加了对信号和图像进行有效编码的需求,并使这种信号的压缩成为存储和通信技术的核心。基于块的离散余弦变换(DCT)已成为大多数图像压缩算法的基础,并已在较早的JPEG标准和MPEG系列视频标准中采用。在过去的十年中,图像编码的研究活动主要集中在离散小波变换(DWT)上,该离散小波变换提供了适合压缩的优雅表示形式,因此它已包含在最新的JPEG-2000标准中。通过对DCT系数进行适当的重新排序,可以在DCT域中应用在小波压缩的情况下开发的有效量化方案。本文的目的是结合两种变换的较好特征,开发一种计算复杂度低的混合图像编码算法。使用单级DWT分解图像,然后将基于块的DCT应用于低通子带。所采用的量化方案是差分减少算法(DR),以获得嵌入式渐进式图像压缩方案。与基于DCT的编码器相比,该方案的性能更好,并且在很大的压缩比范围内都显示出良好的主观性能。

著录项

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 M.S.
  • 年度 2004
  • 页码 86 p.
  • 总页数 86
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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