BMVC IndexA Comparative Evaluation of Active Appearance Model AlgorithmsMatching and AppearanceEfficient Dense Matching for Textured Scenes using Region Growing

Recovering More Classes than Available Bands for Mixed Pixels in Remote Sensing
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M. Faraklioti, M. Petrou

School of Electronic Engineering
Information Technology and Mathematics
University of Surrey
Guildford
Surrey GU2 5XH UK

Contact: m.faraklioti.@ee.surrey.ac.uk, m.petrou.@ee.surrey.ac.uk

Abstract

The classification of sets of mixed pixels can be accomplished by making use of the relationship of higher order moments of the distributions of the pure and mixed classes. As a consequence, the number of equations relating the means of the distributions can be augmented, providing a number of linear equations larger than the number of available sensor bands. Thus, the important advantage the method offers and makes it unique is the fact that more classes than the available bands can be identified. The capabilities and limitations of the method are assessed first by the use of simulated data that closely imitate real data, and also by real data from Landsat images.

Keywords: Mixed Pixels, Mixels, Classification, Multispectral Images
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BMVC IndexA Comparative Evaluation of Active Appearance Model AlgorithmsMatching and AppearanceEfficient Dense Matching for Textured Scenes using Region Growing

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