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.
Highlights
Image de-nosing is the process of filtering or removing noise from an image so that the standard of the image will be okay or the signal noise ratio (SNR) will be high (Liping & Jinfang, 2016)
The results of processed images for de-noising algorithms show that Median filter had higher Peak Signal to Noise Ratio (PSNR) of 47.7 than the Gaussian filter of 31.79, and lower Mean Square Error (MSE) of 1.11 than Gaussian filter of 43.4.It was ascertained that de-noised images with non-linear median filter had better quality than images de-noised by linear Gaussian filter
Evaluation of Filtering Method In order to ascertain the efficiency of the filtering algorithms method for de noising the sign gesture, the filtered images were compared with respect to the original images before filtering, using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) as shown in Figure and Figure respectively
Summary
Image de-nosing is the process of filtering or removing noise from an image so that the standard of the image will be okay or the signal noise ratio (SNR) will be high (Liping & Jinfang, 2016). Image de-noising is very crucial or important task in image processing for the analysis of images. The major goal in image de-noising is to remove the noise from the image in such a way that the original image is distinct. In modern digital image processing, data de-noising is a common problem and it is a major concern of diverse application areas (Astola & Kuosmanen, 1997). Image de-noising is an important stage in image processing in order to improve the performance of the recognition system. There are numerous systems for filtering noise from images (Astola & Kuosmanen, 1997). Progressive works have been done by many researchers, most especially in the area of image processing, this work has majorly focused on discovery appropriate alternatives to the linear filter that are robust or opposed to the occurrence of impulsive noise. The discovery that has received great awareness is median filters. (Juan & Gonzalo 2002)
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call