3D Filtering in Images Corrupted by Mixed Additive-Impulsive Noise
Novel filtering method in images that are contaminated by complex noises consisting of random impulses and additive noise is designed in this paper. Proposed method consists of three stages: detection and filtering of random impulses, following 3D filtering approach based on sparse representation in DCT basis, and final post-processing that uses bilateral filter and edge reconstruction. During numerous experiments, the developed method has confirmed superiority of novel approach in term of visual image quality via human perception as well as in better criteria values, such as PSNR and SSIM for different test images corrupted by complex noise.