High Density Impulse Noise Removal using Advanced Median Filter for Preserving Image Quality Metrics
Maheswaran U1, Vengadapathiraj M2, Manimaran B3, Arunajayashree R4
1Maheswaran U, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India.
2Vengadapathiraj M, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India.
3Manimaran B, Department of Electrical and Electronics Engineering, Rajalakshmi Institute of Technology, Chennai, India.
4ArunaJayashree R, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India.

Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 11909-11914 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9763118419/2019©BEIESP | DOI: 10.35940/ijrte.D9763.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this work, a procedure to remove the high density salt and pepper noise from a corrupted image is developed and to compare the output image with the original image through the image quality metrics. As a common practice the corrupted pixels are replaced by the median of neighboring pixel values by considering a constant number of neighboring pixels. But in this proposed method the corrupted pixels are identified and are replaced by the median of the neighboring pixel values which are adjustable, to preserve and improve the image quality metrics. This method makes a comparison between the corrupted and uncorrupted pixels and performs the median filtering process only on the corrupted ones. In this work a 3×3, 5×5 and 7×7 square neighborhood are used. The output images are observed with low neighborhood as well as high neighborhood pixel values. The calculation of PSNR (Peak Signal to Noise Ratio) and MSE (Mean square error) value for each dimension with different percentages are considered for the comparative analysis.
Keywords: Advanced Median filter, Image Quality Metrics, MSE, PSNR
Scope of the Article: Advanced Computer Networking.