API Build-data JSON Resources
Theme

Choose how MSRBot.io looks on this device.

Auto (match system) Light mode Dark mode

Preference is stored in this browser only.

SMPTE Meetings and Conferences ( October 1996)
[ACTIVE]

Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding

Metadata

Publisher
SMPTE — White Plains, NY
Doc Type
Conference Paper
Content Type
Original Research
Volume
1996, No. 14A, pp. 106–116
Abstract
The paper describes a board-based hardware implementation of a neural algorithm performing vector quantization for very low bit-rate video compression. The Neural Gas model has been chosen for its remarkable properties in terms of both consistency (quality of the quantization process) and easy implementation. The Neuro-board interfaces to a PC through a standard ISA bus. The system architecture is composed of a 70ns RAM bank, an FPGA-based control logic and mathematical coprocessor, and a DSP device for numerical computations. The board supports both training (codevectors adjustment) and run-time operation. The main advantages of the implemented solution lie in its simplicity and easy control for HW tests and SW development.
Publication Date
1996-10-01
DOI
10.5594/M001241
Link
https://doi.org/10.5594/M001241
Author(s)
Fabio AnconaDept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy
Stefano RovettaDept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy
Rodolfo ZuninoDept. of Biophysical and Electronic Engineering (DIBE), University of Genoa, Via all'Opera Pia 11a, 16145 Genova, Italy
Copyright
© 1996 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

  • [1] Jain A.K. : ‘Image data compression: A review’ , Proc IEEE , Mar. 1981 , vol. 69 , pp. 349 – 389 . EXTERNAL
  • [10] Kohonen T. , Self-organization and Associative Memory , 3rd Ed. , 1989 , Springer Verlag . EXTERNAL
  • [11] Gersho A. Ramamurthi B. , “Image Coding Using Vector Quantization” , in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing , pp. 428 – 431 , May 1982 . EXTERNAL
  • [12] Murakami T. Asai T. Yamakazi E. , “Vector Quantizer of Video Signals” , Electron. Lett. , Vol. 18 , pp. 1005 – 1006 , Nov. 1982 . EXTERNAL
  • [13] Ridella S. Rovetta S. Zunino R. : ‘Generalization-based approach to plastic vector quantization’ Proc. World Congr. on Neur. Net. WCNN'95, Washington , vol. I , pp. 505 – 508 , July 1995 . EXTERNAL
  • [2] Gray R.M. : ‘Source Coding Theory’ , Boston, MA : Kluwer Academic Publishers , 1990 . EXTERNAL
  • [3] Gersho A. : ‘On the structure of vector quantizer’ , IEEE Trans. Inform. Theory , Mar. 1982 , vol. IT-28 , pp. 157 – 162 . EXTERNAL
  • [4] Gray R.M. : ‘Vector Quantization’ , IEEE Acoustics, Speech, and Signal Processing Magazine , Apr. 1984 , pp. 4 – 29 . EXTERNAL
  • [5] Linde Y. Buzo A. Gray R.M. : ‘An algorithm for vector quantizer design’ , IEEE Trans. Commun. , Jan. 1980 , vol. COM-28 , pp. 84 – 95 . EXTERNAL
  • [6] CCITT SGXV, Working party XV/1, specialist group on coding for visual telephony, ‘A comparison between VQ and DCT in RM5 based coding system’, document 359, Sept. 19, 1988 . EXTERNAL
  • [7] Martinetz T. Berkovich S.G. Schulten K. : “Neural Gas” network for vector quantization and its application to time-series prediction’ , IEEE Trans. on Neur. Net. , 1993 , vol.4 , No.4 , pp. 558 – 569 . EXTERNAL
  • [8] Anguita D. Passaggio F. Zunino R. : ‘SOM-based Interpolation to Image Compression’ , Proc World Congr. on Neur. Net. WCNN95 , Washington, vol. I , pp. 739 – 742 , July 1995 . EXTERNAL
  • [9] Nasrabadi N. King R. : ‘Image Coding Using Vector Quantization: A Review’ , IEEE Trans. Commun. , Aug. 1988 , pp. 957 – 971 . EXTERNAL
Source Data (JSON)

Full registry record with provenance metadata. Open directly: /api/doc/10.5594-M001241.json

Reference Tree

Explore all references and references to this document, as a navigable tree.

Open Reference Tree
Reference this Doc

Plain text (ISO 690 compliant)

Preview:
Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996. Available at https://doi.org/10.5594/M001241
Snippet:
Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996. Available at https://doi.org/10.5594/M001241

HTML (ISO 690 compliant)

Preview:
Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996. Available at https://doi.org/10.5594/M001241
Snippet:
<span class="citation">Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; <cite>Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding</cite>, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996. Available at <a href="https://doi.org/10.5594/M001241" target="_blank" rel="noopener">https://doi.org/10.5594/M001241</a></span>

SMPTE Icon SMPTE's HTML Pub

Preview:
Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996
doi: 10.5594/M001241
url: https://doi.org/10.5594/M001241
Snippet:
<li>
Fabio Ancona, Stefano Rovetta, and Rodolfo Zunino; <cite id="bib-10-5594-m001241">Hardware Architectures for Vector Quantization in Very Low Bit-Rate Image Coding</cite>, SMPTE Meetings and Conferences ( October 1996); SMPTE, 1996
<span class="doi">10.5594/M001241</span>
</li>