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An s-layered Grade Decomposition of Images

  • Maria GrzegorekEmail author
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 226)

Abstract

An s-layered model of the grade data analysis is used to image decomposition. The method is derived from grade correspondence analysis and involves grade outliers. Image pixels are described by selected variables. The resulting data table is ordered according to the maximal grade differentiation. The outlying measure from the main trend is calculated for each pixel. This measure defines pixels distances from the regularity. The data table ordered according to outlying measure is divided into more homogeneous subsets and subsets form subimages with more similar pixels (in grade outlier meaning).

Keywords

Concentration Curve Data Table Image Pixel Concentration Index Main Trend 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  1. 1.The Institute of Computer Science PASWarsawPoland

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