Three-stage unstructured filter for removing mixed Gaussian plus random impulse noise

Digital image processing is often contaminated by more than one type of noise, such as mixed noise. In this paper, we propose a three-stage process to develop K-SVD method not only for reducing Gaussian noise but also for mixed Gaussian and impulse noise with optimizing input system and preserving edge structure. A three-stage process is combining of impulse noise removal, edge reconstruction and image smoothing. Pressing of an impulse noise in the early stages by Decision Based Algorithm (DBA) and repairing edge structure by an edge-map are able to optimize the performance of the K-SVD method for smoothing an image. The performance of the filter is analysed in terms of Peak Signal to Noise Ratio (PSNR), Mean Structural Similarity (MSSIM) index and Blind Image Quality Index (BIQI). The simulation result is obtained a significant improvement over the previous research.