Comparison of De-Noising Algorithms Technique

Ogunsanwo Gbenga Oyewole, Goga Nicholas, Awodele Oludele and Okolie Samuel

Network and Communication Technologies, 2017, vol. 3, issue 1, 26

Abstract: The concept of noise appears during the process of gathering the image into digital form- that is when the image is being created and it may also be introduced when the image is being transmitted. The presence of the noise usually degraded the quality of the image. De noising algorithms were employed in order to advance the value of the image. This paper tries to compare linear and non linear filtering algorithm. This study adopted image processing techniques to process 600 images dataset acquired from 60 different signers using vision based method. The acquired images were de-noised using Gaussian filter and Median filter algorithms. The outcomes of the two de-noising algorithms were compared using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The results of processed images for de-noising algorithms show that Median filter had higher PSNR of 47.7 than the Gaussian filter of 31.79, and lower MSE of 1.11 than Gaussian filter of 43.4.It was also ascertained that de-noised images with non-linear median filter had better quality than images de-noised by linear Gaussian filter.

Date: 2017
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