Progressive dimensionality reduction for hyperspectral imagery

Haleh Safavi, Keng Hao Liu, Chein I. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper develops to a new concept, called Progressive Dimensionality Reduction (PDR) which can perform data dimensionality progressive in terms of information preservation. Two procedures can be designed to perform PDR in a forward or backward manner, referred to forward PDR (FPDR) or backward PDR (BPDR) respectively where FPDR starts with a minimum number of spectral-transformed dimensions and increases the spectral-transformed dimension progressively as opposed to BPDR begins with a maximum number of spectral-transformed dimensions and decreases the spectral-transformed dimension progressively. Both procedures are terminated when a stopping rule is satisfied. In order to carry out DR in a progressive manner, DR must be prioritized in accordance with significance of information so that the information after DR can be either increased progressively by FPDR or decreased progressively by BPDR. To accomplish this task, Projection Pursuit (PP)-based DR techniques are further developed where the Projection Index (PI) designed to find a direction of interestingness is used to prioritize directions of Projection Index Components (PICs) so that the DR can be performed by retaining PICs with high priorities via FPDR or BPDR. In the context of PDR, two well-known component analysis techniques, Principal Components Analysis (PCA) and Independent Component Analysis (ICA) can be considered as its special cases when they are used for DR.

Original languageEnglish
Title of host publicationSatellite Data Compression, Communication, and Processing V
DOIs
Publication statusPublished - 2009
EventSatellite Data Compression, Communication, and Processing V - San Diego, CA, United States
Duration: 2009 Aug 42009 Aug 5

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7455
ISSN (Print)0277-786X

Conference

ConferenceSatellite Data Compression, Communication, and Processing V
Country/TerritoryUnited States
CitySan Diego, CA
Period09-08-0409-08-05

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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