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Nonlinear multiscale methods for estimation, approximation, and representation of signals and images.

机译:用于估计,逼近和表示信号和图像的非线性多尺度方法。

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摘要

We cover two topics in the broad area of nonlinear multiscale methods. In the first topic, we develop computationally efficient procedures for solving certain restoration problems in 1-D, including the discrete versions of the total variation regularized problem and the constrained total variation minimization problem. They are based on a simple nonlinear diffusion equation and related to the Perona-Malik equation. A probabilistic interpretation for this diffusion equation in 1-D is provided by showing that it produces optimal solutions to a sequence of estimation problems. We extend our methods to 2-D where they no longer have similar optimality properties; however, we experimentally demonstrate their effectiveness for image restoration.; In the second topic we introduce a new framework of multitree dictionaries and propose new algorithms for efficiently finding the best representation in a multitree dictionary. We apply our framework to develop novel dynamic programming algorithms for finding the best basis in a dictionary of arbitrary lapped bases in 1-D. We illustrate this using a non-dyadic local cosine dictionary, and show that the resulting representations are more compact and are characterized by lower costs and approximate shift-invariance. We also provide an algorithm which is strictly shift-invariant and several accelerated versions of the basic algorithm which explore various tradeoffs between computational efficiency and adaptability. A novel dictionary which constructs the best local cosine representation in the frequency domain is proposed and shown to be better suited for representing certain types of signals. We apply our framework in 2-D to develop novel tree-pruning algorithms for finding the best basis in an arbitrary multitree dictionary. We illustrate our framework through several examples, including a novel block image coder which significantly outperforms both the standard JPEG and quadtree-based methods, and is comparable to embedded coders such as JPEC2000 and SPIHT.
机译:我们在非线性多尺度方法的广泛领域涵盖了两个主题。在第一个主题中,我们开发了计算有效的过程来解决一维中的某些还原问题,包括总变化正则化问题和约束总变化最小化问题的离散版本。它们基于简单的非线性扩散方程,并且与Perona-Malik方程有关。通过显示一维扩散方程产生一系列估计问题的最优解,从而提供了概率解释。我们将方法扩展到不再具有相似的最优性的二维方法。但是,我们通过实验证明了它们在图像复原中的有效性。在第二个主题中,我们介绍了一个新的多树字典框架,并提出了新的算法,可以有效地找到多树字典中的最佳表示形式。我们应用我们的框架来开发新颖的动态规划算法,以便在一维任意重叠碱基的字典中找到最佳基础。我们使用非二进位局部余弦字典对此进行了说明,并表明所得表示形式更加紧凑,并且具有较低的成本和近似的移不变性。我们还提供了严格平移不变的算法和基本算法的多个加速版本,该版本探讨了计算效率与适应性之间的各种折衷。提出了一种新颖的字典,该字典在频域中构造了最佳的局部余弦表示,并且显示出更适合表示某些类型的信号。我们将我们的框架应用于二维中,以开发新颖的树修剪算法,以在任意多树字典中找到最佳基础。我们通过几个示例来说明我们的框架,其中包括新颖的块图像编码器,该编码器明显优于标准JPEG和基于四叉树的方法,并且可与JPEC2000和SPIHT等嵌入式编码器相媲美。

著录项

  • 作者

    Huang, Yan.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 100 p.
  • 总页数 100
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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