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Fast Non-Local Means (NLM) Computation With Probabilistic Early Termination

Ramanathan Vignesh, Byung Tae Oh, C.-C. Jay Kuo
2010 IEEE Signal Processing Letters  
Index Terms-Non-local means (NLM) algorithm, image denoising, probabilistic algorithm, early termination, fast algorithm.  ...  A speed up technique for the non-local means (NLM) image denoising algorithm based on probabilistic early termination (PET) is proposed.  ...  CONCLUSION A probabilistic early termination (PET) scheme for fast NLM computation was presented in this work.  ... 
doi:10.1109/lsp.2009.2038956 fatcat:lxkgogxnlzhrrhouy4rwatyl7u

Survey in Existing Non-Local Means Algorithm for Noise Reduction

Arti Singh, Ram Singar
2017 International Journal of Computer Applications  
For this problem, we study non-local means algorithm. In this algorithm uses a self-similarity concept, called "non-local means algorithm".  ...  In this paper, only survey on the existing non-local means algorithm for noise reduction which is taken from many devices like camera or other digital gadgets.  ...  Probabilistic Early Termination used for fast NON LOCAL MEAN computation If partial sum of distortion term increase with pre-defined threshold. So terminate the computation of distortion.  ... 
doi:10.5120/ijca2017913751 fatcat:bfzl67xvl5gqnikkwk3kkblbxi

Probabilistic Non-Local Means

Yue Wu, Brian Tracey, Premkumar Natarajan, Joseph P. Noonan
2013 IEEE Signal Processing Letters  
In this paper, we propose a so-called probabilistic non-local means (PNLM) method for image denoising.  ...  Encouraging improvements are also found when we replace the NLM weights with the probabilistic weights in tested NLM variants.  ...  INTRODUCTION Non-local means (NLM) is a popular data-adaptive image denoising technique introduced by Buades et al. [1] , [2] .  ... 
doi:10.1109/lsp.2013.2263135 fatcat:ytwz43umrzbzhjea5qnadt6llm

Defense Strategy of Network Security based on Dynamic Classification

2016 KSII Transactions on Internet and Information Systems  
In this paper, a speed-up technique for the non-local means (NLM) image denoising method based on local binary descriptor (LBD) is proposed.  ...  In the NLM, most of the computation time is spent on searching for non-local similar patches in the search window.  ...  Recent NLM speed-up algorithms include modified multi-resolution pyramid architecture [13] and probabilistic early termination (PET) [14] .  ... 
doi:10.3837/tiis.2016.02.021 fatcat:auubo7k6nza4bagesb3bo4orq4

A Correlation Based Strategy for the Acceleration of Nonlocal Means Filtering Algorithm

Junfeng Zhang, Jiasong Wu, Jean-Louis Coatrieux, Limin Luo, Yang Chen
2016 Mathematical Problems in Engineering  
Although the nonlocal means (NLM) algorithm takes a significant step forward in image filtering field, it suffers from a high computational complexity.  ...  To deal with this drawback, this paper proposes an acceleration strategy based on a correlation operation.  ...  Also, some Probabilistic Early Termination (PET) schemes, such as cluster tree, Singular Value Decomposition (SVD), or dictionaries for image blocks and image edges, were also employed to speed up the  ... 
doi:10.1155/2016/5483485 fatcat:ly6dozjv3fgdjnnhpfute2ew3y

Improved Non-Local Means Algorithm Based on Dimensionality Reduction [chapter]

Golam M. Maruf, Mahmoud R. El-Sakka
2015 Lecture Notes in Computer Science  
Most of the computational time for Non-Local Means is consumed to measure patch similarity.  ...  Non-Local Means is an image denoising algorithm based on patch similarity. It compares a reference patch with the neighboring patches to find similar patches.  ...  [7] proposed a speed up technique for the Non-Local Means algorithm based on a probabilistic early termination (PET).  ... 
doi:10.1007/978-3-319-20801-5_5 fatcat:pjkcri6qrjc5xlh77rvqsl5ht4

Recursive non-local means filter for video denoising

Redha A. Ali, Russell C. Hardie
2017 EURASIP Journal on Image and Video Processing  
In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM).  ...  Here, we propose a novel recursive NLM (RNLM) algorithm for video processing. Our RNLM method takes advantage of recursion for computational savings, compared with the direct 3D NLM.  ...  The non-local means (NLM) algorithm [3] for image denoising has received significant attention in the image processing community.  ... 
doi:10.1186/s13640-017-0177-2 fatcat:djnxhdnjp5gh7mxts4vwqdajqu

A Downsampled SAR-BM3D Despeckling Approach for Single-Look SAR Images in High Resolution

Wuchao Wang, Xiaolin Liu, Wenlong Zhang
2016 Journal of Computer and Communications  
Keywords Despeckling, SAR-BM3D, Downsampling, High Resolution, Synthetic Aperture Radar (SAR) 2005, inspired by the local filtering, Buades et al. proposed non-local means method How to cite this paper  ...  However, when tackling with high resolution SAR images, it often has an unsatisfying despeckling performance in the homogeneous smooth regions, together with a high time complexity.  ...  Adaptive search size selecting, probabilistic early termination and look-up table are adapted in FANS (Fast adaptive nonlocal SAR despeckling) [9] to speed up SAR-BM3D.  ... 
doi:10.4236/jcc.2016.415012 fatcat:owy54uy6rrec7evxbxszkywnqu

Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering

Stanley H. Chan, Todd Zickler, Yue M. Lu
2014 IEEE Transactions on Image Processing  
We propose a randomized version of the non-local means (NLM) algorithm for large-scale image filtering.  ...  The new algorithm, called Monte Carlo non-local means (MCNLM), speeds up the classical NLM by computing a small subset of image patch distances, which are randomly selected according to a designed sampling  ...  Most of these can be traced back to the non-local means (NLM) denoising algorithm of Buades et al. [1] , [2] proposed in 2005.  ... 
doi:10.1109/tip.2014.2327813 pmid:25122743 fatcat:q5cjw47svfg7lpvia7vtnwx7pi

Abductive Knowledge Induction From Raw Data [article]

Wang-Zhou Dai, Stephen H. Muggleton
2021 arXiv   pre-print
To the best of our knowledge, Meta_Abd is the first system that can jointly learn neural networks from scratch and induce recursive first-order logic theories with predicate invention.  ...  However, they suffer from the exponential computational complexity within the interface between these two components, where the sub-symbolic learning model lacks direct supervision, and the symbolic model  ...  The second author acknowledges support from the UK's EPSRC Human-Like Computing Network, grant EP/R022291/1, for which he acts as director.  ... 
arXiv:2010.03514v2 fatcat:6mtsp6ucvnafnme47sama6vuru

Efficient and robust model-to-image alignment using 3D scale-invariant features

Matthew Toews, William M. Wells
2013 Medical Image Analysis  
CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space.  ...  Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D.  ...  with an encoding of local image appearance.  ... 
doi:10.1016/j.media.2012.11.002 pmid:23265799 pmcid:PMC3606671 fatcat:23642cgtsrg2rmghgyugaaxfh4

Maybe Deep Neural Networks are the Best Choice for Modeling Source Code [article]

Rafael-Michael Karampatsis, Charles Sutton
2019 arXiv   pre-print
A major issue with these techniques is that code introduces new vocabulary at a far higher rate than natural language, as new identifier names proliferate.  ...  This means that [37] a token level NLM with a vocabulary of only 76K tokens required a few days to be trained on the smaller training corpus.  ...  Essentially, this means that the additional training data helps our NLM learn to synthesize identifiers from subword units better and with higher confidence.  ... 
arXiv:1903.05734v1 fatcat:lql53s3x4zdf5d7nsv5h2jnw54

A Novel Image Denoising Algorithm Using Concepts of Quantum Many-Body Theory [article]

Sayantan Dutta, Adrian Basarab, Bertrand Georgeot, Denis Kouamé
2022 arXiv   pre-print
In recent years, with the growth of computing power, data-driven strategies exploiting the redundancy within patches extracted from one or several images to increase sparsity have become more prominent  ...  Based on patch analysis, the similarity measures in a local image neighborhood are formalized through a term akin to interaction in quantum mechanics that can efficiently preserve the local structures  ...  Later on, various schemes were proposed in the literature to accelerate or to improve the NLM performance, such as a fast NLM algorithm with a probabilistic early termination [18] , quadtree-based NLM  ... 
arXiv:2112.09254v2 fatcat:cufibbr36jd4rdvvx5gvludkaq

Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration

Sema Candemir, Stefan Jaeger, Kannappan Palaniappan, Jonathan P. Musco, Rahul K. Singh, Zhiyun Xue, Alexandros Karargyris, Sameer Antani, George Thoma, Clement J. McDonald
2014 IEEE Transactions on Medical Imaging  
The National Library of Medicine (NLM) is developing a digital chest x-ray (CXR) screening system for deployment in resource constrained communities and developing countries worldwide with a focus on early  ...  A critical component in the computer-aided diagnosis of digital CXRs is the automatic detection of the lung regions.  ...  Sonia Qasba, Medical Director of Montgomery County's TB Control program, for providing us with the Montgomery dataset and medical advice. We thank Dr. Chetan S.  ... 
doi:10.1109/tmi.2013.2290491 pmid:24239990 fatcat:bohmwjq56bc7lklwch47qruudy

Deep Learning of Representations: Looking Forward [chapter]

Yoshua Bengio
2013 Lecture Notes in Computer Science  
Whereas previous ways of dealing with the output bottleneck involved non-distributed word classes, we introduce a distributed representation for discrete word classes along with techniques to turn an apparently  ...  relatively slow computations because of the so-called output bottleneck arising from the need to compute and normalize probabilities over all the words in the vocabulary.  ...  He is also grateful for the funding support from NSERC, CIFAR, the Canada Research Chairs, and Compute Canada.  ... 
doi:10.1007/978-3-642-39593-2_1 fatcat:xad2okhdkrfbrhe4ilujsnoqlu
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