Classification by using wavelet transform on multispectral images

Hai-Hui Wang; Ai-Ping Cai

doi:10.1117/12.713266

28 October 2006 Classification by using wavelet transform on multispectral images

Hai-Hui Wang, Ai-Ping Cai

Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64191R (2006) https://doi.org/10.1117/12.713266
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China

Abstract

This study analyzed texture features in multi-spectral image data. Recent development in the mathematical theory of wavelet transform has received overwhelming attention by the image analysts. An evaluation of the ability of wavelet transform and other texture analysis algorithms in feature extraction and classification was performed in this study. The algorithms examined were the wavelet transform, spatial co-occurrence matrix, fractal analysis, and spatial autocorrelation. The performance of the above approaches with the use of different feature was investigated. Wavelet transform was found to be far more efficient than other advanced spatial methods.

Citation Download Citation

Hai-Hui Wang and Ai-Ping Cai "Classification by using wavelet transform on multispectral images", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64191R (28 October 2006); https://doi.org/10.1117/12.713266

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