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Adaptive multiresolution image and video compression and pre/post-processing of image and video streams.

机译:自适应多分辨率图像和视频压缩以及图像和视频流的预处理/后处理。

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摘要

his thesis is divided into two sections. In the first section, the focus is on adaptive transform-based image compression and motion compensation at low bit rates. In the second section, the pre-processing and post-processing of images and video streams are focused on.;Natural images are two dimensional signals with unknown or time-varying characteristics. For this type of signal, linear expansion with a fixed set of basis functions is not flexible enough to represent the data with the desired degree of accuracy. For example, the Fourier transform is not a good fit for regions with sharp discontinuities such as edges, and the wavelet transform is not a good fit for regions with periodic high-frequency components such as localized textures or stripes. In the first section a new adaptive algorithm for image representation and coding is introduced. This algorithm is based on the concept of segmented orthogonal matching pursuits (SOMP), and adaptively selects the best representation from an overcomplete dictionary of wavelet functions.;In the second section, a new robust nonlinear filter based on the theory of generalized maximum likelihood and order statistics (GMLOS) is introduced. It is shown that this filter is an
机译:他的论文分为两个部分。在第一部分中,重点是低比特率的基于自适应变换的图像压缩和运动补偿。在第二部分中,着重于图像和视频流的预处理和后处理。自然图像是具有未知或时变特性的二维信号。对于此类信号,具有一组固定基函数的线性扩展不够灵活,无法以所需的准确度表示数据。例如,傅立叶变换不适用于诸如边缘等尖锐不连续的区域,而小波变换不适用于具有周期性高频分量(例如局部纹理或条纹)的区域。在第一部分中,介绍了一种新的用于图像表示和编码的自适应算法。该算法基于分段正交匹配追踪(SOMP)的概念,并从小波函数的超完备字典中自适应地选择最佳表示。第二部分,基于广义最大似然和引入了订单统计(GMLOS)。显示该过滤器是

著录项

  • 作者

    Rabiee, Hamid R.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 1996
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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