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Interpretable Low-Dimensional Regression via Data-Adaptive Smoothing [article]

Wesley Tansey, Jesse Thomason, James G. Scott
2017 arXiv   pre-print
To address this problem, we present Maximum Variance Total Variation denoising (MVTV), an approach that is conceptually related both to CART and to the more recent CRISP algorithm, a state-of-the-art alternative  ...  method for interpretable nonlinear regression.  ...  MVTV involves two main steps: (1) a novel maximum-variance heuristic to create a data-adaptive grid over the feature space; and (2) smoothing over this grid using a fast total variation denoising algorithm  ... 
arXiv:1708.01947v1 fatcat:qiy7pqhwz5dzjavj5wz6552fqm

A manually denoised audio-visual movie watching fMRI dataset for the studyforrest project

Xingyu Liu, Zonglei Zhen, Anmin Yang, Haohao Bai, Jia Liu
2019 Scientific Data  
To make neural-related signals stand out from the noise, the audio-visual movie watching fMRI dataset from the project was denoised by a combination of spatial independent component analysis and manual  ...  ., artifacts) that makes searching for the signals induced by specific cognitive processes significantly challenging.  ...  After denoising, the ISC from the Fig. 2 2 Artifact ICs accounted for a large proportion of ICs and variances in both smoothed (left column) and unsmoothed (right column) fMRI data.  ... 
doi:10.1038/s41597-019-0303-3 pmid:31784528 pmcid:PMC6884625 fatcat:ps5hmcmahbdglkzlmjgvxjh3b4

Hyperspectral Image Denoising Based on Nonlocal Low-rank and TV Regularization

Xiangyang Kong, Yongqiang Zhao, Jize Xue, Jonathan Cheung-Wai Chan, Zhigang Ren, HaiXia Huang, Jiyuan Zang
2020 Remote Sensing  
In addition, a regularization strategy with spatial–spectral total variation (SSTV) is utilized to ensure the global spatial–spectral smoothness in both spatial and spectral domains.  ...  Our method is designed to model the spatial–spectral non-local self-similarity and global spatial–spectral smoothness simultaneously.  ...  Acknowledgments: We are grateful to the authors of the compared methods for providing the source codes. Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/rs12121956 fatcat:dns7jhinafckddevoyl4v7fzma

Non-Local Means Denoising of Dynamic PET Images

Joyita Dutta, Richard M. Leahy, Quanzheng Li, Arrate Muñoz-Barrutia
2013 PLoS ONE  
Finally, we use a spatially varying smoothing parameter based on a local variance approximation over each spatiotemporal patch.  ...  Objective: Dynamic positron emission tomography (PET), which reveals information about both the spatial distribution and temporal kinetics of a radiotracer, enables quantitative interpretation of PET data  ...  The spatial variation of the smoothing parameter is based on a local variance approximation over each spatiotemporal patch.  ... 
doi:10.1371/journal.pone.0081390 pmid:24339921 pmcid:PMC3855264 fatcat:p45mz6ypkjetflpnk6wt3pm3fm

GapTV: Accurate and Interpretable Low-Dimensional Regression and Classification [article]

Wesley Tansey, James G. Scott
2017 arXiv   pre-print
To address this problem, we present GapTV, an approach that is conceptually related both to CART and to the more recent CRISP algorithm, a state-of-the-art alternative method for interpretable nonlinear  ...  Our method is fully data-adaptive, in that it incorporates highly robust routines for tuning all hyperparameters automatically.  ...  a fast total variation denoising algorithm (Barbero & Sra, 2014 ).  ... 
arXiv:1702.07405v1 fatcat:6utxds4fqrdvrdd32efz6xxxza

Multiple Wavelet Basis Image Denoising Using Besov Ball Projections

H. Choi, R.G. Baraniuk
2004 IEEE Signal Processing Letters  
Projecting an image onto a Besov ball of proper radius corresponds to a type of wavelet shrinkage for image denoising.  ...  We propose a new image denoising algorithm that exploits an image's representation in multiple wavelet domains.  ...  For maximum denoising performance, we must use the wavelet basis that provides the sparsest representation [1] , [3] .  ... 
doi:10.1109/lsp.2004.833493 fatcat:ntt5zu477rg5jdo3jd5c224c5u

Adaptive Regularization of the NL-Means: Application to Image and Video Denoising

Camille Sutour, Charles-Alban Deledalle, Jean-Francois Aujol
2014 IEEE Transactions on Image Processing  
We develop this model for image denoising and we adapt it to video denoising with 3D patches. Index Terms-Non-local means, total variation regularization, image and video denoising, adaptive filtering  ...  Denoising can also be performed by total variation minimization -the ROF model -which leads to restore regular images, but it is prone to over-smooth textures, staircasing effects, and contrast losses.  ...  One of the most famous variational models used for image denoising is the ROF model [1] that minimizes the total variation (TV) of the image, hence pushing the image towards a piecewise constant solution  ... 
doi:10.1109/tip.2014.2329448 pmid:24951687 fatcat:o6ykq3bpevfvfb5mgokd4ey4fm

Efficient Denoising Technique for CT images to Enhance Brain Hemorrhage Segmentation

H. S. Bhadauria, M. L. Dewal
2012 Journal of digital imaging  
The suggested approach fuses the images denoised by total variation (TV) method, denoised by curvelet-based method, and edge information extracted from the noise residue of TV method.  ...  The visual interpretation shows that the proposed approach not only reduces the staircase effect caused by total variation method but also reduces visual distortion induced by curvelet transform in the  ...  Total Variation-Based Method The total variation-based image denoising method was introduced by ROF [6] .  ... 
doi:10.1007/s10278-012-9453-y pmid:22274942 pmcid:PMC3491154 fatcat:4mdyi2jsozadpfyca4i7evxn4u

Variable Bandwidth Image Denoising Using Image-based Noise Models

Noura Azzabou, Nikos Paragios, Frederic Guichard, Frederic Cao
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
This paper introduces a variational formulation for image denoising based on a quadratic function over kernels of variable bandwidth.  ...  These kernels are scale adaptive and reflect spatial and photometric similarities between pixels.  ...  Variational Image Denoising Total variation minimization has been a dominant formulation for image denoising.  ... 
doi:10.1109/cvpr.2007.383216 dblp:conf/cvpr/AzzabouPGC07 fatcat:reclm6xl4rbztia2ptdf4nklte

Qualitative and Quantitative Evaluation of Image Denoising Techniques

Charandeep Singh Bedi, Himani Goyal
2010 International Journal of Computer Applications  
Moreover there is a long list of image denoising techniques. But problem is that which technique is to be used and for what kind of format.  ...  In this paper, we have discussed various spatial filters in chapter 1. The comparison of the results gives the conclusion and the future scope of the discussion.  ...  The approach presented here is totally based upon the comparison of the above said spatial filters for speckle reduction based on the CoC, PSNR and S/MSE parameters.  ... 
doi:10.5120/1313-1775 fatcat:6jau5allbfgudjlgrb4k2ncn7y

A sensor-data-based denoising framework for hyperspectral images

Ferdinand Deger, Alamin Mansouri, Marius Pedersen, Jon Y. Hardeberg, Yvon Voisin
2015 Optics Express  
A spatially and spectrally adaptive total variation regularisation term accounts the structural proposition of a hyperspectral image cube.  ...  The subsequent denoising is based on an extended variational denoising model, which is suited for a Poisson distributed noise.  ...  [6] extended a variational denoising model to HSI using a spectral-spatial adaptive total variation (TV) semi-norm.  ... 
doi:10.1364/oe.23.001938 pmid:25836066 fatcat:56z6lwohe5f2toymt63oahkr4y

Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

Stanley Chan, Omar Elgendy, Xiran Wang
2016 Sensors  
In this paper, we present a non-iterative image reconstruction algorithm for QIS.  ...  reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising  ...  Fossum for inviting us to submit this work. We thank Neale Dutton and his team for sharing the "fan" and the "milk" sequences collected by their SPAD camera.  ... 
doi:10.3390/s16111961 pmid:27879687 pmcid:PMC5134620 fatcat:jgd5xj36sjetrp7tgxlrzzjlj4

Frequency-Based Separation of Climate Signals [chapter]

Alexander Ilin, Harri Valpola
2005 Lecture Notes in Computer Science  
The rotated sources give a meaningful representation of the slow climate variability as a combination of trends, interannual oscillations, the annual cycle and slowly changing seasonal variations.  ...  Components exhibiting slow temporal behaviour were extracted using DSS with linear denoising.  ...  Rich Pawlowicz for providing the mapping toolbox for Matlab.  ... 
doi:10.1007/11564126_53 fatcat:hjgh7i6tyrhs3kkqzzjnt7a5w4

Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping [article]

Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner
2020 arXiv   pre-print
In this paper, we extend this model in two ways: (1) by introducing a joint total variation (JTV) prior on the intercepts and decay, and (2) by deriving a nonlinear maximum a posteriori estimate.  ...  In this validation, we outperformed other state-of-the-art methods and additionally showed that the proposed approach greatly reduces the variance of the estimated maps, without introducing bias.  ...  Smoothing can be used to improve SNR, but at the cost of lower spatial specificity. Denoising methods aim to separate signal from noise.  ... 
arXiv:2005.14247v1 fatcat:qfr4yxvcvzbmnowjozmrupyyau

A Review on Noise and Denoise of Biometric Images

Jyotsna Singh
2018 International Journal for Research in Applied Science and Engineering Technology  
Hence this study offers knowledge of noise and its types and also briefly defines the general denoising techniques for biometric images.  ...  In our work we mainly focused on denoising of biometric images such as MRI and USI images.  ...  Total Variation The perception behind denoising of image based on total variation is that the noise-free images have lower discrete image gradient than the noisy images.  ... 
doi:10.22214/ijraset.2018.3037 fatcat:3ycahz3dubhvbgd554logha7fy
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