Image Denoising Using Edge Model-based Representation of Laplacian Subbands

Abstract

This paper presents a novel method of removing unstructured, spurious artifacts (more popularly called noise) from images. This method uses an edge model-based representation of Laplacian subbands and deals with noise at Laplacian subband levels to reduce it effectively. As the prominent edges are retained in their original form in the denoised images, the proposed method can be classified as an edge preserving denoising scheme. Laplacian subbands are represented using a Primitive Set (PS) consisting of 7 x 7 subimages of sharp and blurred Laplacian edge elements. The choice of edge model-based representation provides greater flexibility in removing characteristic artifacts from noise sources.