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Denoising 3D Medical Images Using a Second Order Variational Model and Wavelet Shrinkage [chapter]

Minh-Phuong Tran, Renaud Péteri, Maitine Bergounioux
2012 Lecture Notes in Computer Science  
The proposed method is based on a second order variational model and an undecimated wavelet thresholding operator.  ...  The aim of this paper is to construct a model which decomposes a 3D image into two components: the first one containing the geometrical structure of the image, the second one containing the noise.  ...  The proposed method is based on a second order variational model and an undecimated wavelet thresholding operator.  ... 
doi:10.1007/978-3-642-31298-4_17 fatcat:75htk4uyinainm3j4zduxlkgsi

Computing with Curvelets: From Image Processing to Turbulent Flows

Jianwei Ma, Gerlind Plonka
2009 Computing in science & engineering (Print)  
The curvelet transform is a multiscale and multidirectional transform, which allows an almost optimal non-adaptive sparse representation for curve-like features and edges.  ...  In this paper, we describe some recent applications involving image processing, seismic data exploration, turbulent flows, and compressed sensing.  ...  Fig. 4 shows a comparison of image denoising by Daubechies DB4 wavelet shrinkage, contourlet shrinkage, curvelet shrinkage, and the TV-constraint curvelet shrinkage with 25 iterations.  ... 
doi:10.1109/mcse.2009.26 fatcat:xnkio7jrorbptbfgog77alt2di

Image decomposition using a second-order variational model and wavelet shrinkage

Minh-Phuong Tran
2019 ELCVIA Electronic Letters on Computer Vision and Image Analysis  
It also continues the idea introduced previously by authors in [Denoising 3D medical images using a second order variational model and wavelet shrinkage, Imag.  ...  The ROF2 model was first proposed by Bergounioux et al. in [A second-order model for image denoising, Set-Valued Anal. and Var.  ...  In particular, the second-order space BV 2 shows convincing results in image denoising [12] , and in image texture extraction [13] .  ... 
doi:10.5565/rev/elcvia.1162 fatcat:mx4je7m5ijfq5gobdmcsz5wt34

MULTIRESOLUTION ANALYSIS USING WAVELET TRANSFORMS FOR MEDICAL IMAGE SEGMENTATION

2020 Journal of Critical Reviews  
It is particularly a challenging task to classify cancers in human organs in scanners output using shape or gray-level information; organs shape changes throw different slices in medical stack and the  ...  The goal of the paper is in (i) the presentation of the three-dimensional wavelet transform, (ii) discussion of its use for volume data denoising, and (iii) proposal of the following data extraction to  ...  Our work is based on two methods: a second-order variational minimization model and the wavelet transform, which applications in image processing are image restoration, segmentation, decomposition strategies  ... 
doi:10.31838/jcr.07.15.367 fatcat:47p5ac65ynfylhq4c3i6sscxri

Smooth Adaptation by Sigmoid Shrinkage

Abdourrahmane M. Atto, Dominique Pastor, Grégoire Mercier
2009 EURASIP Journal on Image and Video Processing  
This paper addresses the properties of a subclass of sigmoid-based shrinkage functions: the non zeroforcing smooth sigmoid-based shrinkage functions or SigShrink functions.  ...  It provides a SURE optimization for the parameters of the SigShrink functions. The optimization is performed on an unbiased estimation risk obtained by using the functions of this subclass.  ...  The second model is a "signalindependent" model obtained by applying a logarithmic transform to the noisy image. We begin with the speckle signal-dependent model.  ... 
doi:10.1155/2009/532312 fatcat:ato6jsobdfae7hhv72xgxo5gk4

Approximate Message Passing in Coded Aperture Snapshot Spectral Imaging [article]

Jin Tan, Yanting Ma, Hoover Rueda, Dror Baron, Gonzalo Arce
2015 arXiv   pre-print
The simulation results show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST  ...  The approximate message passing (AMP) framework is utilized to reconstruct hyperspectral images from CASSI measurements, and an adaptive Wiener filter is employed as a three-dimensional image denoiser  ...  Rangan and P. Schniter for inspiring discussions on approximate message passing; L. Carin, and X. Yuan for kind help on numerical experiments; J.  ... 
arXiv:1509.02427v1 fatcat:o6y5funuc5f67nkfdbi6qxk57m

Image Denoising Based on Wavelet Analysis for Satellite Imagery [chapter]

Parthasarathy Subashini, Marimuthu Krishnaveni
2012 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology  
Unlike most existing denoising algorithms, using the SURE makes it needless to hypothesize a statistical model for the noiseless image.  ...  www.intechopen.com Image Denoising Based on Wavelet Analysis for Satellite Imagery 451 3. to propose wavelet concept for describing the denoising of images using shrinkage methods 4. to produce a case  ... 
doi:10.5772/36140 fatcat:peb56kehereajkjpp3ieixw3xy

Approximate message passing in coded aperture snapshot spectral imaging

Jin Tan, Yanting Ma, Hoover Rueda, Dror Baron, Gonzalo R. Arce
2015 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)  
The simulation results show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST  ...  The approximate message passing (AMP) framework is utilized to reconstruct hyperspectral images from CASSI measurements, and an adaptive Wiener filter is employed as a three-dimensional image denoiser  ...  Rangan and P. Schniter for inspiring discussions on approximate message passing; L. Carin, and X. Yuan for kind help on numerical experiments; J.  ... 
doi:10.1109/globalsip.2015.7418268 dblp:conf/globalsip/TanMRBA15 fatcat:uc5uckykvbelrjrck6glauc2om

PATCH-BASED NONLOCAL DENOISING FOR MRI AND ULTRASOUND IMAGES

Xin Li
2007 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
Unlike conventional denoising techniques based on local models, a patch-based nonlocal image model is presented and its applications into restoring medical images are demonstrated.  ...  A nonlocal denoising algorithm based LLT thresholding and adaptive fusion is proposed for removing Rician noise from MRI data and speckle noise from ultrasound images.  ...  Q = N + 1 patches in the order of monotonically increasing distance and pack them into a noisy 3D array Y; -denoise Y by LLT-based thresholding to obtain denoised version Ŷ; • Unpack the 3D array Ŷ to  ... 
doi:10.1109/isbi.2007.357010 dblp:conf/isbi/Li07 fatcat:zszfbwkfzjg5dm644ai3vjojaq

Compressive Hyperspectral Imaging via Approximate Message Passing

Jin Tan, Yanting Ma, Hoover Rueda, Dror Baron, Gonzalo R. Arce
2016 IEEE Journal on Selected Topics in Signal Processing  
AMP is an iterative algorithm that can be used in signal and image reconstruction by performing denoising at each iteration.  ...  We employed an adaptive Wiener filter as the image denoiser, and called our algorithm "AMP-Wiener."  ...  ACKNOWLEDGMENTS We thank Sundeep Rangan and Phil Schniter for inspiring discussions on approximate message passing; Lawrance Carin, and Xin Yuan for kind help on numerical experiments; Junan Zhu for informative  ... 
doi:10.1109/jstsp.2015.2500190 fatcat:7xxng5l4wrc5bmwuhogc4lrad4

Denoising of DT-MR Images with an Iterative PCA

U. Sreelakshmi Priya, Jyothisha J. Nair
2015 Procedia Computer Science  
During MR image acquisition the emitted energy is converted to image by using some mathematical models, and this may cause addition of noise. Therefore we need to denoise the image.  ...  In this paper, we propose a denoising technique that uses Structural Similarity Index Matrix (SSIM) for grouping similar patches and performs Iterative Principal Component Analysis on each group.  ...  M.R Kaimal, Chairman, Department of Computer Science, for his valuable suggestions and also to Dr. Kesavadas, Associate Professor, SCTIMST for his guidance and support. Our special thanks to Mrs.  ... 
doi:10.1016/j.procs.2015.08.079 fatcat:dptqhcgwt5h23a6qos5oh5tdca

Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques

T K Senthil Kumar, E N Ganesh
2013 International Journal of Biomedical Science  
Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels.  ...  Wavelet tool also let us to compress the original CT image to greater factor without any sacrifice in accuracy of nodule detection.  ...  De-noise using un-decimated Wavelet transform Developing Image denoising algorithms is a difficult task since fine details in a medical image embedding diagnostic information should not be destroyed during  ... 
pmid:23675284 pmcid:PMC3644416 fatcat:3j7456i3q5d3hlshi3ipcuu4yq

An Extensive Review of Significant Researches on Medical Image Denoising Techniques

Mredhula. L, M. A. Dorairangasamy
2013 International Journal of Computer Applications  
Hence, denoising of medical images is indispensable. Researchers have recognized this issue and have provided lots of paradigms and techniques for use in the medical image denoising process.  ...  In this day and age, digital images play a significant role in our day-to-day life. Digital images are utilized in a wide range of fields like medical, business and more.  ...  Based on a combination of the total variation minimization scheme and the wavelet scheme a denoising algorithm for medical images has been proposed by YangWang et al. [77] .  ... 
doi:10.5120/10699-1551 fatcat:qq7ijy7r7zdhnesrdjow7ucsxq

Soft Autoencoder and Its Wavelet Adaptation Interpretation [article]

Fenglei Fan, Mengzhou Li, Yueyang Teng, Ge Wang
2021 arXiv   pre-print
Furthermore, we propose a generalized linear unit (GenLU) to make an autoencoder more adaptive in nonlinearly filtering images and data, such as denoising and deblurring.  ...  Consequently, Soft-AE can be naturally interpreted as a learned cascaded wavelet shrinkage system.  ...  Wavelet Shrinkage Denoising: Donoho and Johnstone [27] proposed the wavelet shrinkage algorithm, which was theoretically proved with optimal denoising properties.  ... 
arXiv:1812.11675v4 fatcat:6qc46dhblbhkbcqsmdf6gmywg4

Proposed technique for accurate detection/segmentation of lung nodules using spline wavelet techniques

T.K. Senthil Kumar, E.N. Ganesh
2022 figshare.com  
Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels.  ...  Wavelet tool also let us to compress the original CT image to greater factor without any sacrifice in accuracy of nodule detection.  ...  De-noise using un-decimated Wavelet transform Developing Image denoising algorithms is a difficult task since fine details in a medical image embedding diagnostic information should not be destroyed during  ... 
doi:10.6084/m9.figshare.19881772.v1 fatcat:w7szdnf5gbd2blhblrcgah2nue
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