Multi-threshold image denoising based on shearlet transform

Shearlet is a new effective signal representation tool in many image applications. A novel image denoising scheme based on Shearlet transform is proposed in this paper. The original image is first decomposed using shearlet transform, then the shrink threshold of each decomposed subband adopts the different best threshold, producing the preliminary primary denoised image after reconstruction. Experiments show that the proposed scheme can remove the pseudo-Gibbs artifacts and image noise effectively. Besides, it outperforms the existing schemes in regard of both the peak-signal-to-noise-ratio (PSNR) and the edge preservation ability.