Performance evaluation of a new local edge profile preservation based denoising algorithm

Abstract

Denoising digital images while preserving sharp details and fine edges is an active area of research. This paper presents novel local edge profile detection and preservation based denoising algorithm for digital images in presence of zero mean Gaussian noise. Detecting and preserving sharp changes in image pixel intensities preserves the visual quality of the denoised image. Twenty four different types and orientations of edges are detected in 3×3 overlapping tiles of a picture. Based on the edge type and orientation, each tile is subjected to integration along the direction of the detected edge. This preserves the edges. Simple averaging is done if a tile does not have any edge. Continuity of edges is maintained by taking the overlapping tiles of the same edge and integrating both the neighbouring tiles in the direction of the edge. The integration across the edges are avoided to preserve the sharpness of the edges. The proposed algorithm is benchmarked with other denoising algorithms in terms of a novel edge representation parameter i.e. number of edge tiles in the input image. The proposed algorithm clearly outperforms the other contemporary algorithms. Most of the other algorithms either over construct or under construct the edges during denoising.