Improved Sparse matrix Denoising Techniques using affinity matrix for Geographical Images

Authors

  • Mandeep Kaur Yadavindra College of Engineering, Talwandi Sabo, Bathinda, India
  • Balkrishan Jindal Yadavindra College of Engineering, GKC, Punjabi University, Talwandi Sabo, Bathinda, India

Keywords:

Image denoising, Geographical images, Gaussian noise, Sparse Matrix method

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.

 

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Published

2017-10-30

How to Cite

[1]
M. Kaur and B. Jindal, “Improved Sparse matrix Denoising Techniques using affinity matrix for Geographical Images”, Int. J. Sci. Res. Comp. Sci. Eng., vol. 5, no. 5, pp. 51–56, Oct. 2017.

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Section

Research Article

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