High density noise reduction of tea leaves using density mass filter (DMF)

Abstract

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.