Open AccessDesign of Decision Based Recursive Weighted Median Filter With Exponential Weights
Author(s) -
Motepalli Siva Rama Ganesh,
Kalyan Sagar Kadali,
Ramu Bhukya,
Y.T.R. Palleswari,
A. Subramaniya Siva,
S. Pragaspathy
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2089/1/012016
Subject(s) - median filter , mathematics , weighted median , impulse noise , exponential function , algorithm , noise (video) , impulse (physics) , filter (signal processing) , mean squared error , weighted arithmetic mean , statistics , computer science , artificial intelligence , image (mathematics) , image processing , computer vision , mathematical analysis , physics , pixel , quantum mechanics
The prescribed algorithm for removing impulse noise effectively even under high noise densities without causing any loss of image details. Hence a cascaded section of median filters that, involves an Decision-based Median Filter followed by a Recursive Weighted Median (RWM) Filter employing exponential weights are used. The median controlled algorithm is employed to calculate the exponential weights. In the algorithms that where proposed in earlier which involves a cascaded section of the median with the RWM filters provided lesser Peak Signal/Noise Ratio (PSNR) and greater Mean Square Error(MSE) values. Hence the output appeared to be distorted for higher noise levels. These drawbacks have been eliminated in this proposed algorithm.