Results 1 to 10 of about 2,171 (69)

Remote Sensing Image Enhancement Based on Non-Local Means Filter in NSCT Domain

open access: yesAlgorithms, 2017
In this paper, a novel remote sensing image enhancement technique based on a non-local means filter in a nonsubsampled contourlet transform (NSCT) domain is proposed.
Liangliang Li, Yujuan Si, Zhenhong Jia
doaj   +3 more sources

Improved Non-local Means Filtering Algorithm [PDF]

open access: yesJisuanji gongcheng, 2016
The non-local means filtering algorithm is an efficient denoising algorithm that can restore details of image texture well.However,the algorithm cannot adaptive adjust filtering parameters and the filtering result is easy to produce artifacts.Owing to ...
GUO Beibei,YI Sanli,HE Jianfeng,MIAO Ying,SHAO Dangguo
doaj   +1 more source

Quantitative and Comparative Analysis of Effectivity and Robustness for Enhanced and Optimized Non-Local Mean Filter Combining Pixel and Patch Information on MR Images of Musculoskeletal System

open access: yesSensors, 2021
In the area of musculoskeletal MR images analysis, the image denoising plays an important role in enhancing the spatial image area for further processing. Recent studies have shown that non-local means (NLM) methods appear to be more effective and robust
Jan Kubicek   +5 more
doaj   +1 more source

Entropy-Based Non-Local Means Filter for Single-Look SAR Speckle Reduction

open access: yesRemote Sensing, 2022
Speckle is an interference phenomenon that contaminates images captured by coherent illumination systems. Due to its multiplicative and non-Gaussian nature, it is challenging to eliminate.
Debora Chan   +2 more
doaj   +1 more source

Non-Local Means Hole Repair Algorithm Based on Adaptive Block

open access: yesApplied Sciences, 2023
RGB-D cameras provide depth and color information and are widely used in 3D reconstruction and computer vision. In the majority of existing RGB-D cameras, a considerable portion of depth values is often lost due to severe occlusion or limited camera ...
Bohu Zhao, Lebao Li, Haipeng Pan
doaj   +1 more source

Non-Local Means De-Speckling Based on Multi-Directional Local Plane Inclination Angle

open access: yesRemote Sensing, 2023
The unavoidable speckle in SAR images seriously interferes with image quality and has a negative effect on subsequent image interpretation. The existing filters still need to be strengthened in terms of both noise suppression and edge preservation. Based
Fengcheng Guo, Haoran Tang, Wensong Liu
doaj   +1 more source

Noise Reduction in ECG Signal Using an Effective Hybrid Scheme

open access: yesIEEE Access, 2020
Electrocardiogram (ECG) is a critical biological signal, which usually carries a great deal of essential information about patients. The high quality ECG signals are always required for a proper diagnosis of cardiac disorders.
Pingping Bing   +3 more
doaj   +1 more source

SAR Image Segmentation by Efficient Fuzzy C-Means Framework with Adaptive Generalized Likelihood Ratio Nonlocal Spatial Information Embedded

open access: yesRemote Sensing, 2022
The existence of multiplicative noise in synthetic aperture radar (SAR) images makes SAR segmentation by fuzzy c-means (FCM) a challenging task. To cope with speckle noise, we first propose an unsupervised FCM with embedding log-transformed Bayesian non ...
Jingxing Zhu, Feng Wang, Hongjian You
doaj   +1 more source

Non-Local Means Denoising

open access: yesImage Processing On Line, 2011
We present in this paper a new denoising method called non-local means. The method is based on a simple principle: replacing the color of a pixel with an average of the colors of similar pixels. But the most similar pixels to a given pixel have no reason
Antoni Buades   +2 more
doaj   +1 more source

Parameter-Free Fast Pixelwise Non-Local Means Denoising

open access: yesImage Processing On Line, 2014
This article proposes a fast and open-source implementation of the well-known Non-Local Means (NLM) denoising algorithm, in its original pixelwise formulation.
Jacques Froment
doaj   +1 more source

Home - About - Disclaimer - Privacy