Lifting Wavelet Fusion Based ALOS Image Land Cover Classification
CAO Min
BIAN Zheng-fu
Abstract：According to the principle of lifting wavelet transform theory, the lifting wavelet transform image fusion model for extracting the basic information of land use/land cover from remote sensing image is proposed by combining the advantages of wavelet transform fusion and Intensity Hue Saturation transform (IHS transform) fusion. By taking an example of Japanese advanced Land Observation Satellite (ALOS) image in the north shore of the Yangtze River es-tuary, it is concluded that the lifting wavelet transform image fusion model is better than the traditional method through combining subjective and objective indicators comprehensive evalua-tion and image classification Kappa Coefficients. The lifting wavelet fusion model can improve the image spatial resolution and maintain image spectral information at the same time. So the model effectively improves the interpretation accuracy of extracting the basic land use/land cov-er information from remote sensing images.
Keywords：lifting waveletimage fusionland use/land coverimage classificationkappa co-efficient
Publication Date：2009-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 655-659 )