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

  • Authors

    • Nur Aimi Abdul Aziz
    • Suhaila Abd Halim
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.33.23473
  • Anisotropic Diffusion, Douglass-Gunn ADI, Image Denoising, MATLAB, Noise.

  • 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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  • How to Cite

    Aimi Abdul Aziz, N., & Abd Halim, S. (2018). Application of Douglass-Gunn ADI Scheme on Diffusion Model with Different Noise Level for Image Denoising. International Journal of Engineering & Technology, 7(4.33), 10-13. https://doi.org/10.14419/ijet.v7i4.33.23473