Improved Sparse matrix Denoising Techniques using affinity matrix for Geographical Images

Mandeep Kaur¹ , Balkrishan Jindal²

1. Yadavindra College of Engineering, Talwandi Sabo, Bathinda, India.
2. Yadavindra College of Engineering, GKC, Punjabi University, Talwandi Sabo, Bathinda, India.

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.5 , pp.51-56, Oct-2017

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v5i5.5156

Online published on Oct 30, 2017

Copyright © Mandeep Kaur, Balkrishan Jindal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
In this paper, noise is removed from geographical images. In this method affinity matrix is used to find the similarity between pixels in an image then traverse the image. Initial position of the pixels applied affinity matrix to compare the adjacent pixels of the image. It is calculates the probability of the pixel store in a matrix. A dissimilar pixel means unwanted or noisy pixels removed from the image as well as denoised the image. The performance of the proposed method is evaluated using Image Quality Measures (IQM) like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) etc.Experimental results shown that the proposed method is better than Sparse Matrix method, Bayes Thresholding method and Bilateral Filter in terms of MSE, PSNR and SSIM.

Key-Words / Index Term :
Image denoising, Geographical images, Gaussian noise, Sparse Matrix method

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