Satellite image denoising using shearlet transform

Satellite images are mostly degraded due to the inaccuracy or limitations of the transmission and storage devices. Removal of noise from satellite images are still a challenging task for many researchers. The conventional image denoising algorithms mostly use wavelet transform. The main limitation of wavelet transform is that it can capture only limited information along different directions. Hence edges in an image get distorted. Satellite image denoising algorithms should not distort edges in an image, as they form the relevant information in the image. In this paper a different approach for satellite image denoising is introduced where the wavelet transform used in the state of art techniques is replaced by shearlet transform. The threshold for denoising is selected using artificial bee colony optimization. On experimental analysis, the proposed method is found to produce superior peak signal-to-noise ratio (PSNR) over the conventional denoising algorithms.