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Poisson Reducing Unilateral Filtering for X-ray Image Denoising

Kirti V. Thakur, Omkar H. Damodare, Ashok M. Sapkal Published in Image Processing

IJAIS Proceedings on International Conference on Communication Computing and Virtualization
Year of Publication: 2016
© 2015 by IJAIS Journal
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  1. Kirti V.thakur, Omkar H.damodare and Ashok M Sapkal. Article: Poisson Reducing Unilateral Filtering for X-ray Image Denoising. IJAIS Proceedings on International Conference on Communication Computing and Virtualization ICCCV 2016(2):9-13, July 2016. BibTeX

    @article{key:article,
    	author = "Kirti V.thakur and Omkar H.damodare and Ashok M. Sapkal",
    	title = "Article: Poisson Reducing Unilateral Filtering for X-ray Image Denoising",
    	journal = "IJAIS Proceedings on International Conference on Communication Computing and Virtualization",
    	year = 2016,
    	volume = "ICCCV 2016",
    	number = 2,
    	pages = "9-13",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

This paper is enhancement of author's earlier work, Poisson noise Reducing Bilateral Filter (PRBF). This paper recommends two major changes in PRBF. One change is to make PRBF independent of distance variance i. e. filter performance is based on single parameter (range variance). Therefore this proposed work is named as Poisson Reducing UnilateralFiltering (PRUF). Similarly, performance of PRBF on edge region is enhanced due to second change and same is demonstrated through experimentation. Peak signal to noise ratio (PSNR) and Structural similarity index matching (SSIM) quality metrics are used for comparison of proposed PRUF with existing PRBF. performance is based on single parameter (range variance). Therefore this proposed work is named as Poisson Reducing UnilateralFiltering (PRUF). Similarly, performance of PRBF on edge region is enhanced due to second change and same is demonstrated through experimentation. Peak signal to noise ratio (PSNR) and Structural similarity index matching (SSIM) quality metrics are used for comparison of proposed PRUF with existing PRBF.

Reference

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Keywords

Poisson noise, X-ray denoising, Bilateral filter, Poisson noise reducing bilateral filter, PSNR, SSIM.