Open AccessHigh Density Noise Reduction of Tea Leaves using Density Mass Filter (DMF)
Author(s) -
Palanivel Velmurugan,
Dr.M.Renuka Devi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k2295.0981119
Subject(s) - salt and pepper noise , median filter , gaussian noise , impulse noise , mean squared error , noise (video) , mathematics , peak signal to noise ratio , noise reduction , computer science , artificial intelligence , image noise , computer vision , pattern recognition (psychology) , statistics , image processing , image (mathematics) , pixel
In agriculture digital image processing play an important role in the prediction of tea leaves diseases. But acquisition of image may be corrupted by various types of noise such as impulse noise, Gaussian noise and salt and pepper noise. These noises can corrupt the image. So it will reduce the quality of the image and it reduces the classification accuracy. Hence it needs a efficient filter to remove these noise. This paper introduced a new filter density mass filter. It reduces all kinds of noise. Two metrics PSNR (Peak Signal to Noise ratio) and RMSE (Root Mean Square Error) values are used to evaluate the quality of images. The PSNR value of proposed filter is significantly high and RMSE value is reasonably low