Compression and Classification of Hyperspectral Images using an Algorithm based on DWT and NTD

Hyperspectral images (HSIs) has become very popular area of research. This paper deals with the compression and classification of Hyperspectral images using Discrete Wavelet Technique in conjunction with Non negative Tucker Decomposition. This algorithm exploits both the spectral and the spatial information of the images. The core idea behind the proposed technique is to apply TD on the DWT coefficients of spectral bands of HSIs. The results obtained by using the proposed method gives a satisfactory performance in terms of PSNR. Classification accuracy of Hyperspectral images is also calculated using the proposed method. It is shown that the classification of Hyperspectral image is affected from the compression of these images.