Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis by Wayne L. MyersPattern-Based Compression of Multi-Band Image Data for Landscape Analysis by Wayne L. Myers

Pattern-Based Compression of Multi-Band Image Data for Landscape Analysis

byWayne L. Myers, Ganapati P. Patil

Paperback | November 19, 2010

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We offer here a non-conventional approach to muhivariate ima- structured data for which the basis is well tested but the analytical ramifi­ cations are still unfolding. Although we do not formally pursue them, there are several parallels with the nature of neural networks. We employ a systematic set of statistical heuristics for modeling multivariate image data in a quasi-perceptual manner. When the human eye perceives a scene, the elements of the scene are segregated heuristically into compo­ nents according to similarity and dissimilarity, and then the relationships among the components are interpreted. Similarly, we segregate or seg­ ment the scene into hierarchically organized components that are subject to subsequent statistical analysis in many modes for interpretive purposes. We refer to the segregated scene segments as patterns, since they provide a basis for perception of pattern. Since they are also hierarchically organ­ ized, we refer to them further as polypatterns. This leads us to our acro­ nym of Progressively Segmented Image Modeling As Poly-Patterns (PSIMAPP). Likewise, we formalize our approach in terms of pattern processes and segmentation sequences. In alignment with the terminology of image analysis, we refer to our multivariate measures as being signal bands.
Dr. Wayne L. Myers earned M.F. and Ph.D. degrees in forest ecology and forest entomology at the University of Michigan. He began his professional career in Canada as a research forest entomologist and biometrician. He then joined the faculty of forestry at Michigan State University specializing in biometrics and remote sensing. The pos...
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Title:Pattern-Based Compression of Multi-Band Image Data for Landscape AnalysisFormat:PaperbackDimensions:190 pages, 23.5 × 15.5 × 0.07 inPublished:November 19, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:1441942718

ISBN - 13:9781441942715

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Table of Contents

Innovative Imaging, Parsing Patterns and Motivating Models.- Pattern Progressions and Segmentation Sequences for IMAGE Intensity Modeling and Grouped Enhancement.- Collective and Composite Contrast for Pattern Pictures.- Content Classification and Thematic Transforms.- Comparative Change and Pattern Perturbation.- Conjunctive Context.- Advanced Aspects and Anticipated Applications.