Paper Info
Title
Improved Probabilistic Decision-Based Trimmed Median Filter For Detection And Removal Of High-Density Impulsive Noise
Abstract
This study focuses on the detection and expulsion of noisy pixels from an image contaminated by impulsive noise. A noise detection approach is developed to avoid the misinterpretation of noise-free pixel as noisy. In order to design the noise removal algorithm, a probabilistic decision-based improved trimmed median filter (PDITMF) algorithm is proposed which is intended to work out the conflict related to the even number of noise-free pixels in the trimmed median filter. It deploys two new estimation techniques for de-noising, namely, improved trimmed median filter (ITMF) and patch else ITMF (PEITMF) as per noise density. At last, the noise detection approach is applied in the proposed PDITMF to build up a new technique called a probabilistic decision-based adaptive improved trimmed median filter (PDAITMF) algorithm. The proposed algorithms, PDITMF and PDAITMF experiment with many standard sample images. Simulation results show the proposed algorithms are capable of detecting and de-noising the contaminated image very efficiently and have a better visual representation. Under the authors' knowledge, the PDAITMF outperforms recently reported algorithms in context to peak signal-to-noise ratio as well as an image enhancement factor with the lower execution time at all noise densities.
Year
DOI
Venue
2020
10.1049/iet-ipr.2019.1240
IET IMAGE PROCESSING
Keywords
DocType
Volume
image enhancement, image denoising, impulse noise, median filters, PDITMF, detecting noising, de-noising, contaminated image, signal-to-noise ratio, noise density, improved probabilistic decision-based trimmed median filter, high-density impulsive noise, expulsion, noisy pixels, -pepper noise, noise detection approach, noise-free pixel, noise removal algorithm, trimmed median filter algorithm
Journal
14
Issue
ISSN
Citations 
17
1751-9659
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Amit Prakash Sen100.34
Nirmal Kumar Rout2243.10