An optimized direction statistics for detecting and removing random-valued impulse noise
type: Item
instance of: scholarly article
title: An optimized direction statistics for detecting and removing random-valued impulse noise
zbMATH Open document ID: 1412.94012
author: Hao Yang
author: Hang Qiu
author: Leiting Chen
published in: Journal of Industrial and Management Optimization
publication date: 2019-02-05T00:00:00Z
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 47A52
zbMATH DE Number: 7012492
zbMATH Keywords: random-valued impulse noise
zbMATH Keywords: weight rank-order differences
zbMATH Keywords: detail-preserving regularization
zbMATH Keywords: image denoising
MaRDI profile type: Publication
full work available at URL: jimo.2017062
OpenAlex ID: W2709224105
cites work: Q4488067
cites work: The dual parameterization approach to optimal least square FIR filter design subject to maximum error constraints
cites work: A new weighted mean filter with a two-phase detector for removing impulse noise
cites work: A variational approach to remove outliers and impulse noise
cites work: Fast, robust total variation-based reconstruction of noisy, blurred images
cites work: A Universal Denoising Framework With a New Impulse Detector and Nonlocal Means
DOI: 10.3934/JIMO.2017062
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description: scientific article; zbMATH DE number 7012492