Linear and Non-linear Inverse Pyramidal Image Representation: Algorithms and Applications

  • Roumen Kountchev
  • Vladimir Todorov
  • Roumiana Kountcheva
Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 29)

Abstract

In the chapter is presented one specific approach for image representation, known as Inverse Pyramid Decomposition (IPD), and its main applications. The chapter is arranged as follows: the Introduction reviews the state of the art, comprising the presentation of various pyramidal decompositions and outlining their advantages and demerits. In the next sections are considered in detail the principles of the IPD based on linear (DFT, DCT, WHT, KLT, etc.) and non-linear transforms: deterministic, based on oriented surfaces, and adaptive, based on pyramidal neural networks. Furthermore, the work introduces the non-recursive and recursive implementations of the IPD. Special attention is paid to the main application areas of the IPD: the image compression (lossless, visually lossless and lossy), the multi-view and the multispectral image representation. Significant part of the chapter is devoted to the evaluation and comparison of the new representation with the famous compression standards JPEG and JPEG2000. In the conclusion are outlined the main advantages of the IPD and the trends for future development and investigations.

Keywords

pyramidal image decomposition reduced inverse spectrum pyramid pyramidal neural network multi-view image representation multispectral images compression 

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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  • Roumen Kountchev
    • 1
  • Vladimir Todorov
    • 2
  • Roumiana Kountcheva
    • 2
  1. 1.Department of Radio Communications and Video TechnologiesTechnical University of SofiaSofiaBulgaria
  2. 2.T&K EngineeringSofiaBulgaria

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