Study of remote sensing image texture analysis and classification using wavelet

In the past one difficulty of texture analysis was the lack of adequate tools to characterize different scales of texture effectively. Recent developments in multiresolution analysis such as the Gabor and wavelet transforms, help to overcome this difficulty. This paper introduces a new approach to characterize texture at multiple scales. The performances of the wavelet transform are measured in terms of sensitivity and selectivity for the classification of 25 types of remote sensing texture relief images under the condition of different wavelet decomposition models, different filter lengths, different resolutions and different mother bodies. The reliability exhibited by texture signatures of wavelet transforms are beneficial for accomplishing segmentation, classification and subtle discrimination of texture.