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Semilogarithmic Nonuniform Vector Quantization of Two-Dimensional Laplacean Source for Small Variance Dynamics

Z. Peric, M. Savic, S. Panic
2012 Radioengineering  
In this paper high dynamic range nonuniform two-dimensional vector quantization model for Laplacean source was provided.  ...  Semilogarithmic A-law compression characteristic was used as radial scalar compression characteristic of two-dimensional vector quantization.  ...  Acknowledgements This paper was supported by the Serbian Ministry of Education and Science (project III44006 and TR32035).  ... 
doaj:93d1a2cfbeb3409c9baa8249de836266 fatcat:7xhavpzik5aqfjvyh4qheg67yq

A review of iris recognition algorithms

Richard Yew Fatt Ng, Yong Haur Tay, Kai Ming Mok
2008 2008 International Symposium on Information Technology  
Due to its reliability and nearly perfect recognition rates, iris recognition is used in high security areas.  ...  A literature review of the most prominent algorithms implemented in each stage is presented.  ...  The normalized iris image is a rectangle image with angular resolution and radial resolution. The iris image has low contrast and non-uniform illumination caused by the position of the light source.  ... 
doi:10.1109/itsim.2008.4631656 fatcat:e2u5tl24ovfjlncducsc5ciwtm

Bidirectional Texture Function Compression Based on Multi-Level Vector Quantization

V. Havran, J. Filip, K. Myszkowski
2010 Computer graphics forum (Print)  
These functions are compressed in turn using a novel multi-level vector quantization algorithm. The result of this algorithm is a set of index and scale code-books for individual dimensions.  ...  The Bidirectional Texture Function (BTF) is becoming widely used for accurate representation of real-world material appearance. In this paper a novel BTF compression model is proposed.  ...  This work has been supported by the Ministry of Education, Youth and Sports of the Czech Republic under the research program MSM 6840770014 and LC-06008 (Center for Computer Graphics), the Aktion Kontakt  ... 
doi:10.1111/j.1467-8659.2009.01585.x fatcat:ysarzp4cm5atlefmdkx7bgywje

A Vision System for Multi-View Face Recognition [article]

M. Y. Shams, A. S. Tolba, S.H. Sarhan
2017 arXiv   pre-print
We utilize Multi-Layer Perceptron (MLP) and combined classifiers based on both Learning Vector Quantization (LVQ), and Radial Basis Function (RBF) for classification purposes.  ...  The variations of face images with respect to different poses are considered as one of the important challenges in face recognition systems.  ...  The proposed system is evaluated using multi-layer perceptron (MLP), combined learning vector quantization (CLVQ), and combined radial basis function (CRBF) based on rank and decision level fusion.  ... 
arXiv:1706.00510v1 fatcat:celx6nr6ybhyplkfeeffxfmwum

Interest Point Detector and Feature Descriptor Survey [chapter]

Scott Krig
2014 Computer Vision Metrics  
The training method allows for a range of descriptor sampling patterns and shapes to be built by weighting and choosing sample points with high variance and low correlation.  ...  The resulting descriptor is a compressed, binary encoded bit vector suitable for Hamming distance.  ... 
doi:10.1007/978-1-4302-5930-5_6 fatcat:3jmbq6bpivfqxaq7mcwbs5t2yy

Bidirectional Texture Function Modeling: A State of the Art Survey

J. Filip, M. Haindl
2009 IEEE Transactions on Pattern Analysis and Machine Intelligence  
However, the appearance of real materials dramatically changes with illumination and viewing variations.  ...  Thus, the only reliable representation of material visual properties requires capturing of its reflectance in as wide range of light and camera position combinations as possible.  ...  A very similar approach, applying a radial basis functions instead of spherical harmonics for pixelwise compression was introduced in [56] . Ma et al.  ... 
doi:10.1109/tpami.2008.246 pmid:19762922 fatcat:qrfnlegr2nhj5brylmhm7tzn5a

Forensic Analysis of Linear and Nonlinear Image Filtering Using Quantization Noise

Hareesh Ravi, A. V. Subramanyam, Sabu Emmanuel
2016 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
Transition probability features extracted from the quantization noise are used for machine learning based detection and classification.  ...  Experiments are performed to compare the performance of the proposed technique with state-of-the-art forensic filtering detection algorithms.  ...  We use Radial Basis Function (RBF) kernel based binary classification Support Vector Machine (SVM) from [Chang and Lin 2011] libsvm library.  ... 
doi:10.1145/2857069 fatcat:p7v2akwlhjhi5efpmepvvqteci

Natural Image Coding in V1: How Much Use Is Orientation Selectivity?

Jan Eichhorn, Fabian Sinz, Matthias Bethge, Li Zhaoping
2009 PLoS Computational Biology  
the first time, complete rate-distortion curves for ICA in comparison with PCA.  ...  This question has not yet been settled, as over the last ten years contradicting results have been reported ranging from less than five to more than hundred percent extra gain for ICA.  ...  Acknowledgments We would like to thank Philipp Berens, Roland Fleming, Jakob Macke and Bruno Olshausen for fruitful discussions and helpful comments on the manuscript. Author Contributions  ... 
doi:10.1371/journal.pcbi.1000336 pmid:19343216 pmcid:PMC2658886 fatcat:kri3giuo3vb7dgy6lbwqbcbb4i

Neural networks expand SP's horizons

S. Haykin
1996 IEEE Signal Processing Magazine  
meet and interact to solve a wide range of problems.  ...  Derivation of exact properties (e.g., mean and variance) of estimators for small sample-sizes; if the exact properties are not mathematically tractable, then one would consider the asymptotic properties  ...  The quantized data were then Huffmancoded with a codebook optimized for Laplacian distributions. The number of bits assigned for the class information was simply log& bits per block.  ... 
doi:10.1109/79.487040 fatcat:ujmpsiax5jdnnnrjo3i6hijxam

Reliability of Static and Dynamic Network Metrics in the Resting-State: A MEG-beamformed Connectivity Analysis [article]

Stavros I Dimitriadis, Bethany Routley, David E Linden, Krish D Singh
2018 biorxiv/medrxiv   pre-print
Although many algorithms for the analysis of brain connectivity have been proposed, the reliability of network metrics derived from both static and dynamic functional connectivity is still unknown.  ...  Here, we first estimated both static (SFC) and dynamic functional connectivity (DFC) after beamforming source reconstruction using the imaginary part of the phase locking index (iPLV) and the correlation  ...  In a recent study, we demonstrated a better modeling of dynamic functional connectivity graphs (DFCG) based on a vector quantization approach (Dimitriadis et al., 2013a) .  ... 
doi:10.1101/358192 fatcat:xcvdd5kmkbcajptxxtnaylsnpe

Reliability of Static and Dynamic Network Metrics in the Resting-State: A MEG-Beamformed Connectivity Analysis

Stavros I. Dimitriadis, Bethany Routley, David E. Linden, Krish D. Singh
2018 Frontiers in Neuroscience  
Although many algorithms for the analysis of brain connectivity have been proposed, the reliability of network metrics derived from both static and dynamic functional connectivity is still unknown.  ...  Here, we first estimated both static (SFC) and dynamic functional connectivity (DFC) after beamforming source reconstruction using the imaginary part of the phase locking index (iPLV) and the correlation  ...  In a recent study, we demonstrated a better modeling of dynamic functional connectivity graphs (DFCG) based on a vector quantization approach (Dimitriadis et al., 2013a) .  ... 
doi:10.3389/fnins.2018.00506 pmid:30127710 pmcid:PMC6088195 fatcat:mpxnhkrhnfe75h3bd67zfukec4

No-reference image and video quality assessment: a classification and review of recent approaches

Muhammad Shahid, Andreas Rossholm, Benny Lövström, Hans-Jürgen Zepernick
2014 EURASIP Journal on Image and Video Processing  
The field of perceptual quality assessment has gone through a wide range of developments and it is still growing.  ...  The NR methods of visual quality assessment considered for review are structured into categories and subcategories based on the types of methodologies used for the underlying processing employed for quality  ...  The primary source of blur in compression techniques is the truncation of high-frequency components in the transform domain of an image.  ... 
doi:10.1186/1687-5281-2014-40 fatcat:caidirehyvd75ml5mobmt7vpoi

Machine learning in acoustics: theory and applications [article]

Michael J. Bianco, Peter Gerstoft, James Traer, Emma Ozanich, Marie A. Roch, Sharon Gannot, Charles-Alban Deledalle
2019 arXiv   pre-print
ML is a broad family of techniques, which are often based in statistics, for automatically detecting and utilizing patterns in data.  ...  With large volumes of training data, ML can discover models describing complex acoustic phenomena such as human speech and reverberation.  ...  ACKNOWLEDGMENTS This work was supported by the Office of Naval Research, Grant No. N00014-18-1-2118.  ... 
arXiv:1905.04418v3 fatcat:xuhykqhrk5bqbg5x7gaajcksay

Image Quality Assessment [chapter]

Kalpana Seshadrinathan, Thrasyvoulos N. Pappas, Robert J. Safranek, Junqing Chen, Zhou Wang, Hamid R. Sheikh, Alan C. Bovik
2009 The Essential Guide to Image Processing  
The Laplacian pyramid of Burt and Adelson [74] is used to decompose the image into seven radial frequency bands.  ...  One good choice is C 1 = (K 1 E) 2 , where E is the dynamic range of the pixel values (255 for 8-bit grayscale images), and K 1 << 1 is a small constant.  ... 
doi:10.1016/b978-0-12-374457-9.00021-4 fatcat:iornqix5cjaffkglvivdlx6gva

On the role and the importance of features for background modeling and foreground detection

Thierry Bouwmans, Caroline Silva, Cristina Marghes, Mohammed Sami Zitouni, Harish Bhaskar, Carl Frelicot
2018 Computer Science Review  
With the availability of a rather large set of invariant features, the challenge is in determining the best combination of features that would improve accuracy and robustness in T. Bouwmans  ...  variation, dynamic camera motion, cluttered background and occlusion.  ...  A radial basis function kernel is used to deal with non-linear input data.  ... 
doi:10.1016/j.cosrev.2018.01.004 fatcat:s6j5766emrcuhhwgkrvkuyy6hy
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