Image denoising method based on grey relational threshold

Abstract

Purpose

The paper aims to do some further research on grey relational analysis applied in wavelet transform, and proposed a grey relational threshold algorithm for image denoising. This study tries to suppress the noise while retaining the edges and important structures as much as possible.

Design/methodology/approach

The paper analyzed the characters of noises and edges distribution in different subbands; then used the grey relational value to calculate the relationship of scale, direction and noise deviation. This paper used the grey relational value of scale, direction and noise deviation as influenced factors, and proposed a grey relational threshold algorithm.

Findings

Grey relational analysis used in threshold setting has the superiority in image denoising. The simulation results have already certified both in visual effect and peak signal to noise ratio (PSNR).

Originality/value

This paper applied grey relation theory into image denoising, and proposed a grey relational threshold algorithm. It provides a novel method for image denoising.

Citation

Hong‐jun, L., Wei, H., Zheng‐guang, X. and Wei, W. (2013), "Image denoising method based on grey relational threshold", Grey Systems: Theory and Application, Vol. 3 No. 2, pp. 191-200. https://doi.org/10.1108/GS-03-2013-0003