Paper
4 November 1996 Classification of spatial patterns using wavelets
Thomas S. Moon
Author Affiliations +
Abstract
The interpretation of airphotos relies heavily on the identification of textures and spatial patterns. The 2-D wavelet transform can be used to quantify simple patterns for automated classification of pixels in an image. The transform generates a set of images similar in format to a multispectral image deck, but based on spatial information localized about each pixel. The images in this 'wavelet' deck each correspond to an analysis of patterns in the original image at different spatial resolutions. For example, where one image in the wavelet deck depends on spatial variations within a 32 by 32 pixel area, the next image in the deck contains information on spatial features within a 16 by 16 pixel area. Individual pixels in the wavelet deck can be classified using the same classification and pattern recognition algorithms used with multispectral images. Classifications based on the wavelet deck of four airphoto samples using a minimum-distance to means algorithm and an artificial neural network are presented.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas S. Moon "Classification of spatial patterns using wavelets", Proc. SPIE 2818, Multispectral Imaging for Terrestrial Applications, (4 November 1996); https://doi.org/10.1117/12.256093
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KEYWORDS
Wavelets

Image classification

Multispectral imaging

Wavelet transforms

Pattern recognition

Artificial neural networks

Detection and tracking algorithms

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