Image denoising method based on PM model with transforming edge stopping function

Yu, Jun; Zhai, Rumeng; Yie, Jiayong

doi:10.1109/itnec.2017.8284769

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Over the years, there are lots of work has been done for image denoising by solving the Anisotropic Diffusion (AD) equation with different DC function. In [13] introduced two DC function and further modification of the Perona and Malik function [6,14,17,3] is developed to enhance the quality of image. In this paper, the higher range of parameter is used and one type of DC function being applied to test the performance of the scheme.…”

Section: Introductionmentioning

confidence: 99%

Application of Douglass-Gunn ADI Scheme on Diffusion Model with Different Noise Level for Image Denoising

Aziz

Halim²

2018

IJET

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Noise level is the amount of noise that corrupted the clear image in order to test on the filtering method of an algorithm proposed for image denoising. Most of the existing filtering techniques are able to remove noise but unable to preserve the image detail well and hence causing the blurring effect. Due to that, the objectives of this paper are to propose and implement Douglas-Gunn Alternating Direction Implicit (DG-ADI) on Anisotropic Diffusion (AD) model. Then, measure the performance of the proposed scheme with different level of noise. PDE based model is applied with the unconditional stable of DG-ADI scheme to remove the noise that corrupted the images. The AD model is used for preserving the image structures and edges. In this paper, a set of grayscale images from standard database is being filtered with three different noise levels in order to measure the performance of the proposed schemes. The performance of the proposed scheme is measured using the Mean Structural Similarity Index (MSSIM), Peak Signal to Noise Ratio (PSNR), Universal Image Quality Index (UIQI) and processing time. The implementation of the algorithm is completed using MATLAB R2013a. Experimental results show that the DG-ADI scheme able to remove noise with different noise level. The used of DG-ADI scheme in solving the AD model can remove the noise well without destroy the structure of image with appropriate parameters setting in grayscale image.

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