Wavelet Compression and the Automatic Classification of Urban Environments using High Resolution Multispectral Imagery and Laser Scanning Data

Citation:
KYALO PROFKIEMAJOHNBOSCO. "Wavelet Compression and the Automatic Classification of Urban Environments using High Resolution Multispectral Imagery and Laser Scanning Data.". In: Journal of Geoinformatica. Kluwer Academic Publishers; 2001.

Abstract:

This paper examines the influence of multisensor data fusion on the automatic extraction of topographic objects from SPOT panchromatic imagery. The suitability of various grey level co-occurence based texture measures, as well as different pixel windows is also investigated. It is observed that best results are obtained with a 3x3 pixel window and the texture measure homogeneity. The synthetic texture image derived together with a Landsat TM imagery are then fused with the SPOT data using the additional channel concept. The object feature base is expanded to include both spectral and spatial features. A maximum likelihood classification approach is then applied. It is demonstrated that the segmentation of topographic objects is significantly improved by fusing the multispectral and texture information.

Notes:

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