Shearlet and Patch Reordering Based Texture Preserving Denoising Method for Locust Slice Images

Locust slice image is a kind of cartoon-like images, in which the texture possesses the property of self-similarity. Both of the texture and the noises belong to the high-frequency signals, and so it is difficult to tell the difference between them for most denoising methods. Aim to the problem, we propose a novel denoising method by combining the patch reordering with the shearlet transform. In the reordering process, the patches are divided into smooth and texture components. The filters obtained from the training set are employed to process the patches in smooth regions and the shearlet transform are employed to process the texture regions. The experiments show that the values of PSNR and SSIM of the processed images obtained by the proposed method are better than the common methods.