De-noising of Hyper-spectral Images in Wavelet Domain with Improved Soft Thresholding

A hyper-spectral image can be corrupted by noise during the transmission process. The noise does not have positive effect on the image, so it is essential to discard the noise before performing analysis to improve the quality of an image. Noise removal is among the important and challenging works for scientists and researchers in the field of image processing. The main objective of noise removal is to enhance the visual quality of the noisy using de-noising techniques. That is why researchers try to discard the noise before they perform further analysis. The main focus of the thesis is removing noise from hyper-spectral remote sensing images. Image de-nosing helps us improve the quality of the image, so we are able to analyze the image properly. In this thesis, we use 2D and 3D-DWT combined with hard and soft thresholding for de-noising hyper-spectral images. De-noising based on DWT introduces weakness such as lack of translation invariance. That is why; we suggest using Un-decimated Wavelet Transform (UWT) which discards the mentioned problem. Additionally, 2D and 3D-UWT with soft and hard thresholding functions were used as part of the proposed de-noising techniques. Finally we propose to use a new method for image de-noising in wavelet domain based on applying a smooth nonlinear soft threshold function on Un-decimated Wavelet Transform. This higher order threshold function is known as the improved soft thresholding function. Here we combined this function with 2D and 3D-UWT. Comparing the performance analysis between 2D-UWT and 3D-UWT using improved soft threshold function shows that 3D version outperforms 2D in terms of PSNR value and visual quality. This technique provides us with higher quality and improvement in PSNR value in comparison with several other methods available for de-noising. The proposed method achieves PSNR improvement by 2.12 dB for band 25 of Indian Pine, 1.29 dB for Cuprite Mining District image, 1.46 dB for Arizona Mining and 1.17dB for Golf of Mexico over de-noising based on 3D-UWT with standard soft thresholding technique. Keywords: Hyperspectral image de-noising, wavelet transform, hard and soft thresholding.