Vector quantization

View this topic in
Vector quantization is a classical quantization technique from signal processing which allows the modeling of probability density functions by the distribution of prototype vectors. (Wikipedia.org)






Conferences related to Vector quantization

Back to Top

2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2019 IEEE International Symposium on Information Theory (ISIT)

Information theory and coding theory and their applications in communications and storage, data compression, wireless communications and networks, cryptography and security, information theory and statistics, detection and estimation, signal processing, big data analytics, pattern recognition and learning, compressive sensing and sparsity, complexity and computation theory, Shannon theory, quantum information and coding theory, emerging applications of information theory, information theory in biology.


2018 24th International Conference on Pattern Recognition (ICPR)

ICPR will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields

  • 2016 23rd International Conference on Pattern Recognition (ICPR)

    ICPR'2016 will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields.

  • 2014 22nd International Conference on Pattern Recognition (ICPR)

    ICPR 2014 will be an international forum for discussions on recent advances in the fields of Pattern Recognition; Machine Learning and Computer Vision; and on applications of these technologies in various fields.

  • 2012 21st International Conference on Pattern Recognition (ICPR)

    ICPR is the largest international conference which covers pattern recognition, computer vision, signal processing, and machine learning and their applications. This has been organized every two years by main sponsorship of IAPR, and has recently been with the technical sponsorship of IEEE-CS. The related research fields are also covered by many societies of IEEE including IEEE-CS, therefore the technical sponsorship of IEEE-CS will provide huge benefit to a lot of members of IEEE. Archiving into IEEE Xplore will also provide significant benefit to the all members of IEEE.

  • 2010 20th International Conference on Pattern Recognition (ICPR)

    ICPR 2010 will be an international forum for discussions on recent advances in the fields of Computer Vision; Pattern Recognition and Machine Learning; Signal, Speech, Image and Video Processing; Biometrics and Human Computer Interaction; Multimedia and Document Analysis, Processing and Retrieval; Medical Imaging and Visualization.

  • 2008 19th International Conferences on Pattern Recognition (ICPR)

    The ICPR 2008 will be an international forum for discussions on recent advances in the fields of Computer vision, Pattern recognition (theory, methods and algorithms), Image, speech and signal analysis, Multimedia and video analysis, Biometrics, Document analysis, and Bioinformatics and biomedical applications.

  • 2002 16th International Conference on Pattern Recognition


More Conferences

Periodicals related to Vector quantization

Back to Top

Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


More Periodicals

Most published Xplore authors for Vector quantization

Back to Top

Xplore Articles related to Vector quantization

Back to Top

On the sizes of Voronoi cells in entropy-constrained vector quantization

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

Voronoi cells for vector quantization subject to an entropy constraint are considered. It is shown that the constraint on the output entropy leads to a weaker and even vanishing dependency of the Voronoi cell's volume on the probability density function. Using some simplifying assumptions like linearization of a small part of the r-dimensional input space and modeling of the cell ...


Sessions: vector quantisation

1988 IEEE International Symposium on Information Theory., 1988

The following topics are dealt with: entropy-constrained vector quantisation; vector source bit allocation; noisy channels; hyperplane testing; optimal binary codeword assignment; speech and image coding; and asymptotically optimal Voronoi structure.<<ETX>>


High-compression of chrominance data by use of segmentation of luminance

2000 10th European Signal Processing Conference, 2000

The paper describes a very simple technique for compression of chrominance data in colour images and video sequences coded at low bit rates. The technique is based on coding of arbitrarily shaped regions, whereby each region is efficiently represented by one value of chrominance which is averaged over the whole region. As the regions are determined on the basis of ...


Session: image coding

1988 IEEE International Symposium on Information Theory., 1988

The following topics are dealt with: two-dimensional source adaptive coding; transform trellis coding; vector quantisation using mirror images; low-bit- rate video-coding stochastic modelling; and colour motion picture transmission.<<ETX>>


IEEE Draft Standard for Advanced Audio Coding

IEEE P1857.2/D3, May 2013, 2012

This standard defines a set of tools to support specific audio coding functions including general audio coding and lossless audio coding. The tool set defined in this standard, in combination provides regular high quality and efficient coding tool sets for compression, decompression, processing, and representing of audio data to save bandwidth for transmission, to save space for storage, to speed ...


More Xplore Articles

Educational Resources on Vector quantization

Back to Top

IEEE.tv Videos

The Josephson Effect: The Original SQUIDs
IMS 2011 Microapps - Vector-Receiver Load Pull - Measurement Accuracy at its Best
IMS 2011 Microapps - Techniques for Validating a Vector Network Analyzer Calibration When Using Microwave Probes
Quantization Without Fine-Tuning - Tijimen Blankevoort - LPIRC 2019
IMS 2011 Microapps - IQ Mixer Measurements: Techniques for Complete Characterization of IQ Mixers Using a Multi-Port Vector Network Analyzer
IMS 2012 Microapps - Passive Intermodulation (PIM) measurement using vector network analyzer Osamu Kusano, Agilent CTD-Kobe
IMS 2012 Microapps - Basic Amplifier Measurements with the RF Vector Network Analyzer (VNA) Taku Hirato, Agilent
Non-Volatile Memory Array Based Quantization - Wen Ma - ICRC San Mateo, 2019
Micro-Apps 2013: Alternative Methods and Optimization Techniques for Vector Modulation
MicroApps: 200W RF Power Amplifer Design using a Nonlinear Vector Network Analyzer and Measured Load-Dependent X-Parameters (2) (Agilent Technologies)
SIMD Programming in VOLK, the Vector-Optimized Library of Kernels
Vladimir Vapnik accepts the IEEE John Von Neumann Medal - Honors Ceremony 2017
Approach to winning solutions - Alexander Goncharenko - LPIRC 2019
The Art of MobileNet Design - Andrew Howard - LPIRC 2019
Designing Efficient On-Device AI - Aakanksha Chowdhery - LPIRC 2019
Micro-Apps Keynote 2013: Modern RF Measurements and How They Drive Spectrum Analyzer Digital IF Processor Design
Visual Wake Words Challenge - Aakanksha Chowdhery - LPIRC 2019
Learning through Deterministic Assignment of Hidden Parameter
The Josephson Effect: The Josephson Volt
Neural Processor Design Enabled by Memristor Technology - Hai Li: 2016 International Conference on Rebooting Computing

IEEE-USA E-Books

  • On the sizes of Voronoi cells in entropy-constrained vector quantization

    Voronoi cells for vector quantization subject to an entropy constraint are considered. It is shown that the constraint on the output entropy leads to a weaker and even vanishing dependency of the Voronoi cell's volume on the probability density function. Using some simplifying assumptions like linearization of a small part of the r-dimensional input space and modeling of the cell shapes as hyperspheres leads to an analytic expression of the quotient of the volumes of two neighboring Voronoi cells. The results confirm the use of entropy coded lattice vector quantizers with optimized reproduction vectors in cases of vanishing dependency and may in other cases be exploited for the design of vector companders to be used in conjunction with lattice vector quantization.

  • Sessions: vector quantisation

    The following topics are dealt with: entropy-constrained vector quantisation; vector source bit allocation; noisy channels; hyperplane testing; optimal binary codeword assignment; speech and image coding; and asymptotically optimal Voronoi structure.<<ETX>>

  • High-compression of chrominance data by use of segmentation of luminance

    The paper describes a very simple technique for compression of chrominance data in colour images and video sequences coded at low bit rates. The technique is based on coding of arbitrarily shaped regions, whereby each region is efficiently represented by one value of chrominance which is averaged over the whole region. As the regions are determined on the basis of reconstructed luminance component, no information upon the segment shapes has to be transmitted. In order to obtain high compression, the set of assigned pairs of chrominance is processed by vector quantization. Experimental results prove high efficiency of the proposed technique.

  • Session: image coding

    The following topics are dealt with: two-dimensional source adaptive coding; transform trellis coding; vector quantisation using mirror images; low-bit- rate video-coding stochastic modelling; and colour motion picture transmission.<<ETX>>

  • IEEE Draft Standard for Advanced Audio Coding

    This standard defines a set of tools to support specific audio coding functions including general audio coding and lossless audio coding. The tool set defined in this standard, in combination provides regular high quality and efficient coding tool sets for compression, decompression, processing, and representing of audio data to save bandwidth for transmission, to save space for storage, to speed up indexing and multimedia search, and to enhance performance when using mixed media for virtual reality and other applications that demand high bandwidth. The target applications and services include but not limited audio transmission, audio recording, internet streaming, and other video/audio enabled services and applications.

  • Subjective performance of spectral excitation coding of speech at 2.4 kb/s

    This paper presents a low rate speech codec (2.4 kb/s) based on a sinusoidal model applied to the excitation signal. A frame classifier in combination with a phase dispersion algorithm allows the same model to be used for voiced as well as unvoiced and transitional sounds. The phase dispersion algorithm significantly improves the perceived quality for all frame classes resulting in more "natural" reconstructed speech. Informal MOS testing indicates that the 2.4 kb/s SEC system achieves MOS scores close to the existing 4 kb/s standards (differences up to 0.2 on the MOS scale) and significantly better than the existing 2.4 kb/s LPC-10 standard (difference of 1.5 on the MOS scale).

  • Codebook Generation Based on Complex Systems

    During the last decades the development of an efficient method for generation and optimization of codebooks for vector quantization is always a big challenge. By taking the advantage of complex systems, we develop a new design of codebook generation. In this paper some improved optimization methods for codebook generation will be discussed.

  • IEE Colloquium 'Low Bit Image Coding' (Digest No.1995/154)

    None

  • Tree-structured lattice vector quantization

    In [14][15] we introduced a new vector quantizer (VQ) for the compression of digital image sequences. Our approach unifies both efficient coding methods : a fast lattice encoding [3] and an unbalanced tree-structured codebook design according to a distortion vs. rate tradeoff [2] [16]. This tree-structured lattice VQ (TSLVQ) is based on the hierarchical packing of embedded truncated lattices. Now we investigate the determination of the most efficient lattice respectively to this method. We also describe a fast test which permits to detect the input vectors whose norm is above than the maximum allowed by the TSLVQ. Finally we analyse experimental results applied to image sequence with our VQ taking place in a region-based coding scheme for a videophone application.

  • Security Analysis on "A Chaotic Fragile Watermarking Technique with Precise Localization"

    Security holes resulting from the independence of pixels in the existing fragile watermarking technique with pixel-precise localization have been pointed out. In this paper, the security of an algorithm with precise localization is analyzed. Vector quantization (VQ) attack, collage attack and oracle attack are implemented on the algorithm. Theoretical analysis and simulation results show that the algorithm has poor security, and is vulnerable to collage attack and oracle attack.



Standards related to Vector quantization

Back to Top

No standards are currently tagged "Vector quantization"


Jobs related to Vector quantization

Back to Top