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Imaging and video compression using embedded zerotree coding.

机译:使用嵌入式零树编码的图像和视频压缩。

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In this dissertation, we investigate several embedded zerotree wavelet (EZW) coding techniques for designing image and video coders. Four topics addressed include: (1) EZW coding using non-uniform quantization, (2) Adaptive EZW coding using rate-distortion criterion, (3) Modified "set partitioning in hierarchical trees" (SPIHT) and (4) Video coding using segmentation, regional wavelet packet, and adaptive EZW. The first three topics are applications for image compression, and the last topic is an application for video compression.; The embedded zerotree wavelet image compression algorithm developed by Shapiro is the most popular wavelet-based image coder to date. First, we aim to modify the quantization characteristics of EZW by the following two approaches: (1) Non-uniform quantizer: we design two non-uniform quantization schemes, nonuniform EZW and Lloyd-Max EZW. (2) Rate-distortion criterion: we develop adaptive EZW, where we introduce adaptive step sizes for each subband. The best set of step sizes is found by using Lagrangian optimization, where two coding environments, independent and dependent, are considered.; The proposed image coder retains all the good features of EZW, namely, embedded coding, progressive transmission, order of importance. Experimental results show that the proposed image coders perform significantly better than the standard EZW algorithm.; Then, we aim at the significance map coding of EZW by designing a new set partition algorithm. We adopt and modify the framework of the SPIHT. The new set partition algorithm can catch more insignificant coefficients than the original algorithm. The experimental results show that the proposed algorithms achieve significant improvement over the standard EZW and SPIHT algorithms.; Finally, we present a new video coding algorithm. This algorithm can effectively exploit the temporal, spatial and frequency information within a video sequence through a combination of segmentation, regional wavelet packet, adaptive EZW, and DPCM techniques. The proposed video coder provides notable improvement in R-D characteristics over similar algorithms.
机译:本文研究了几种嵌入式零树小波(EZW)编码技术,用于设计图像和视频编码器。涉及的四个主题包括:(1)使用非均匀量化的EZW编码,(2)使用速率失真准则的自适应EZW编码,(3)修改的“层次树中的集合划分”(SPIHT)和(4)使用分段的视频编码,区域小波包和自适应EZW。前三个主题是图像压缩的应用程序,最后一个主题是视频压缩的应用程序。 Shapiro开发的嵌入式零树小波图像压缩算法是迄今为止最流行的基于小波的图像编码器。首先,我们旨在通过以下两种方法来修改EZW的量化特性:(1)非均匀量化:我们设计了两种非均匀量化方案,即EZW和Lloyd-Max EZW。 (2)速率失真准则:我们开发了自适应EZW,其中我们为每个子带引入了自适应步长。通过使用拉格朗日优化,可以找到最佳的步长集,其中考虑了两个编码环境,独立和相关。提出的图像编码器保留了EZW的所有良好功能,即嵌入式编码,渐进式传输,重要性顺序。实验结果表明,所提出的图像编码器的性能明显优于标准的EZW算法。然后,通过设计一种新的集合划分算法,针对EZW的重要性图编码。我们采用并修改了SPIHT的框架。与原始算法相比,新的集划分算法可以捕获更多无关紧要的系数。实验结果表明,与标准的EZW和SPIHT算法相比,该算法具有明显的改进。最后,我们提出了一种新的视频编码算法。该算法可以通过分割,区域小波包,自适应EZW和DPCM技术的组合有效地利用视频序列中的时间,空间和频率信息。所提出的视频编码器相对于类似算法在R-D特性方面提供了显着改进。

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