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Stochastic wavelet-based image modeling using factor graphs and its application to denoising

S. Xiao, I. Kozintsev, K. Ramchandran
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)  
In this work, we introduce a hidden Markov field model for wavelet image coefficients within a subband and apply it to the image denoising problem.  ...  The notion of factor graphs is related to other graphical models, such as Bayesian networks and Markov Random Fields and is naturally suited for the models proposed in this paper.  ...  Acknowledgement The authors wish to thank Vladimir Pavlovic for providing us MEX C-code version of the EM algorithms to train the hidden Markov models.  ... 
doi:10.1109/icassp.2000.859271 dblp:conf/icassp/XiaoKR00 fatcat:clhdgrzl6nh73pcv7ppidhlxmm

Variational Bayesian image processing on stochastic factor graphs

Xin Li
2008 2008 15th IEEE International Conference on Image Processing  
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs).  ...  Unlike previous probabilistic graphical models, we model the structure of FGs by a latent variable, which gives the name "stochastic factor graphs"(SFGs).  ...  In this paper, we attempt to set patch-based image processing on a rigorous ground using the language of factor graphs (FGs).  ... 
doi:10.1109/icip.2008.4712113 dblp:conf/icip/Li08 fatcat:bucq6gw6nfgmnezghq56cmmgqa

Image Denoising for AWGN Corrupted Image Using OWT and Thresholding

Shruti Badgainya, Prof. Pankaj Sahu, Prof. Vipul Awasthi
2018 International Journal of Trend in Scientific Research and Development  
A new algorithm based on the orthonormal wavelet transform (OWT) is developed. In this work images corrupted by AWGN are denoised.  ...  The proposed Orthonormal wavelet transform (OWT) method has minimum Mean Square & highest PSNR with Coif let Simulation results shows that denoised image is 98.29 % similar for 5 dB noise standard deviation  ...  Wavelets can also model speech, music, video and non-stationary stochastic signals.  ... 
doi:10.31142/ijtsrd18338 fatcat:b6dxg3f3lbe5tmwxoytlganrkq

A Hybrid Image Denoising Method

Hari Om, Mantosh Biswas
2012 International Journal of Computer Applications  
The LAWML is doubly stochastic process models which denoise an image by exploiting the dependency of local wavelet coefficients within each scale. The LAWML needs a global optimal neighboring window.  ...  It uses a suboptimal universal threshold and identical neighbouring window size in all wavelet subbands.  ...  WAVELET ANALYSIS Wavelet-based tools are now indispensable in many areas of modern statistics, especially in regression, density and function estimation, factor analysis, modeling and forecasting of time  ... 
doi:10.5120/9262-3439 fatcat:xf33n3a3pvhglmeioy4f3yadfm

A Novel Gray Image Denoising Method Using Convolutional Neural Network

Yizhen Meng, Jun Zhang
2022 IEEE Access  
Based on it, Khmag et al. designed an image denoising algorithm based on Principle Component Analysis (PCA) and second-generation wavelet transform [100] .  ...  set of 128 × 2,400 images of 53 × 53 pixels by data augmentation, and adding stochastic noise with standard deviation σ ∈ [0, 60] to it to train the network model.  ... 
doi:10.1109/access.2022.3169131 fatcat:uom37pgrk5hebmasts4jamwj2q

Using Nonlinear Diffusion Model to Identify Music Signals

Qiang Li, Miaochao Chen
2021 Advances in Mathematical Physics  
According to the inherent self-similarity of the music signal system and the completeness and stability of the empirical mode decomposition (EMD) algorithm, a new kind of EMD music using stochastic differentiation  ...  Because it can accurately model the music signal, it solves many complicated problems in music signal processing.  ...  We focus on the simple and practical wavelet threshold denoising method, and aiming at the shortcomings of its threshold denoising, we propose a denoising method based on wavelet transform and Wiener filtering  ... 
doi:10.1155/2021/2210953 fatcat:wmsk4x3nv5azhodntwmg736rxu

Denoising based on wavelets and deblurring via self-organizing map for Synthetic Aperture Radar images [article]

Mario Mastriani
2016 arXiv   pre-print
Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur.  ...  First, we use an original technique for noise reduction in wavelet domain.  ...  Most simple nonlinear thresholding rules for wavelet based denoising assume that the wavelet coefficients are independent [17] - [19] .  ... 
arXiv:1608.00274v1 fatcat:5zhuqledu5cfpayotjzmonvag4

Random cascades on wavelet trees and their use in analyzing and modeling natural images

Martin J. Wainwright, Eero P. Simoncelli, Alan S. Willsky, Akram Aldroubi, Andrew F. Laine, Michael A. Unser
2000 Wavelet Applications in Signal and Image Processing VIII  
In particular, we develop an efficient technique for estimation, and demonstrate in a denoising application that it preserves natural image structure (e.g., edges).  ...  Our framework generates global yet structured image models, thereby providing a unified basis for a variety of applications in signal and image processing, including image denoising, coding, and super-resolution  ...  It is this form of wavelet estimator that we use in our application to image denoising in Section 5.  ... 
doi:10.1117/12.408598 fatcat:tk234alsxvcornd3qlvlz3ymle

Improving gene-network inference with graph-wavelets and making insights about ageing associated regulatory changes in lungs [article]

Shreya Mishra, Vibhor Kumar
2020 bioRxiv   pre-print
Here we devise a conceptually different method using graph-wavelet filters for improving gene-network (GWNet) based analysis of the transcriptome.  ...  Using gene-regulatory-networks based approach for single-cell expression profiles can reveal unprecedented details about the effects of external and internal stress on cells.  ...  He has applied Graph signal processing on protein structures and gene-expression data-sets. Shreya Mishra is a PhD student at computational biology department in IIIT Delhi, India.  ... 
doi:10.1101/2020.07.24.219196 fatcat:rww7gelmojd5zihj3p4ciyleby

Random Cascades on Wavelet Trees and Their Use in Analyzing and Modeling Natural Images

Martin J. Wainwright, Eero P. Simoncelli, Alan S. Willsky
2001 Applied and Computational Harmonic Analysis  
In particular, we develop an efficient technique for estimation, and demonstrate in a denoising application that it preserves natural image structure (e.g., edges).  ...  Our framework generates global yet structured image models, thereby providing a unified basis for a variety of applications in signal and image processing, including image denoising, coding, and super-resolution  ...  It is this form of wavelet estimator that we use in our application to image denoising in Section 5.  ... 
doi:10.1006/acha.2000.0350 fatcat:dzbaaastsfelnjpn6aj66cuzn4

Fields of Experts

Stefan Roth, Michael J. Black
2009 International Journal of Computer Vision  
We demonstrate the capabilities of this Field-of-Experts model with two example applications, image denoising and image inpainting, which are implemented using a simple, approximate inference scheme.  ...  While the model is trained on a generic image database and is not tuned toward a specific application, we obtain results that compete with specialized techniques.  ...  Example Applications To illustrate the capabilities of the Field-of-Experts model as a prior model of images, we demonstrate its use in experiments on image denoising and image inpainting.  ... 
doi:10.1007/s11263-008-0197-6 fatcat:xefw35ijtbew5huoek7w56chfa

Wavelet-based statistical signal processing using hidden Markov models

M.S. Crouse, R.D. Nowak, R.G. Baraniuk
1998 IEEE Transactions on Signal Processing  
Wavelet-based statistical signal processing techniques such as denoising and detection typically model the wavelet coefficients as independent or jointly Gaussian.  ...  To demonstrate the utility of wavelet-domain HMM's, we develop novel algorithms for signal denoising, classification, and detection.  ...  In wavelet-based signal and image processing, we process the signal by operating on its wavelet coefficients and scaling coefficients .  ... 
doi:10.1109/78.668544 fatcat:agm3p7vbkjfardbtqrara3wn64

Denoising Based On Wavelets And Deblurring Via Self-Organizing Map For Synthetic Aperture Radar Images

Mario Mastriani
2008 Zenodo  
Then, the learning of a Kohonen self-organizing map (SOM) is performed directly on the denoised image to take out it the blur.  ...  First, we use an original technique for noise reduction in wavelet domain.  ...  Silvano Zanutto, Director of the Biomedical Engineering Institute, at University of Buenos Aires for his help and support.  ... 
doi:10.5281/zenodo.1059728 fatcat:eq54kwa555d6npxw7glweegrie

Bayesian Learning of Sparse Multiscale Image Representations

James Michael Hughes, Daniel N. Rockmore, Yang Wang
2013 IEEE Transactions on Image Processing  
The associated image model allows us to use a single set of adapted dictionary atoms that is shared-and learned-across all scales in the model.  ...  We apply the proposed model to several common image processing problems including non-Gaussian and nonstationary denoising of real-world color images.  ...  For these real-world images, we estimated the noise level as input to the K-SVD and GSM-based models using the wavelet-based noise level estimation method suggested in [48] .  ... 
doi:10.1109/tip.2013.2280188 pmid:24002002 fatcat:ax5fb2phh5f3df67rbqnmfnanu

Machine Learning Techniques and Applications For Ground-based Image Analysis [article]

Soumyabrata Dev, Bihan Wen, Yee Hui Lee, Stefan Winkler
2016 arXiv   pre-print
We demonstrate the advantages of using machine learning techniques in ground-based image analysis via three primary applications -- segmentation, classification, and denoising.  ...  The images captured by whole sky imagers can have high spatial and temporal resolution, which is an important pre-requisite for applications such as solar energy modeling, cloud attenuation analysis, local  ...  This is why ground-based sky imagers have become popular and are now widely used in these and other applications.  ... 
arXiv:1606.02811v1 fatcat:k5n7u7lynzd4tciedcw54wdv2m
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