NDLI: Constrained-storage vector quantization with a universal codebook

Content Provider	IEEE Xplore Digital Library
Author	Ramakrishnan, Sangeeta Rose, K. Gersho, A.
Copyright Year	1995
Description	Author affiliation: Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA (Sangeeta Ramakrishnan; Rose, K.; Gersho, A.)
Abstract	Many compression applications consist of compressing multiple sources with significantly different distributions. In the context of vector quantization (VQ) these sources are typically quantized using separate codebooks. Since memory is limited in most applications, a convenient way to gracefully trade between performance and storage is needed. Earlier work addressed this problem by clustering the multiple sources into a small number of source groups, where each group shares a codebook. As a natural generalization, we propose the design of a size-limited universal codebook consisting of the union of overlapping source codebooks. This framework allows each source codebook to consist of any desired subset of the universal codevectors and provides greater design flexibility which improves the storage-constrained performance. Further advantages of the proposed approach include the fact that no two sources need be encoded at the same rate, and the close relation to universal, adaptive, and classified quantization. Necessary conditions for optimality of the universal codebook and the extracted source codebooks are derived. An iterative descent algorithm is introduced to impose these conditions on the resulting quantizer. Possible applications of the proposed technique are enumerated and its effectiveness is illustrated for coding of images using finite-state vector quantization.
Starting Page	42
Ending Page	51
File Size	553068
Page Count	10
File Format	PDF
ISBN	0818670126
ISSN	10680314
DOI	10.1109/DCC.1995.515494
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-03-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Image coding Image storage Application software Application specific integrated circuits Signal resolution Space technology Random access memory Iterative algorithms Rate-distortion
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Constrained-storage vector quantization with a universal codebook

Multiresolution tree structured vector quantization

An iterative joint codebook and classifier improvement algorithm for finite-state vector quantization

Adaptive vector quantization using generalized threshold replenishment

Extension of two-stage vector quantization-lattice vector quantization

A vector quantizer with increased codebook patterns

Predictive vector quantization with ridge regression

Vector quantization for entropy coding of image subbands

Image-adaptive vector quantization in an entropy-constrained framework

Constrained-storage vector quantization with a universal codebook

Similar Documents

Constrained-storage vector quantization with a universal codebook

Multiresolution tree structured vector quantization

An iterative joint codebook and classifier improvement algorithm for finite-state vector quantization

Adaptive vector quantization using generalized threshold replenishment

Extension of two-stage vector quantization-lattice vector quantization

A vector quantizer with increased codebook patterns

Predictive vector quantization with ridge regression

Vector quantization for entropy coding of image subbands

Image-adaptive vector quantization in an entropy-constrained framework

Constrained-storage vector quantization with a universal codebook