NDLI: A theoretical exposition to apply the lamda methodology to vector quantization

Content Provider	IEEE Xplore Digital Library
Author	Guzman, E. Zambrano, J.G. Orantes, A. Pogrebnyak, O.
Copyright Year	2009
Description	Author affiliation: Centro de Investigación en Computación, IPN, Mexico (Pogrebnyak, O.) \|\| Universidad Tecnológica de la Mixteca, Mexico (Guzman, E.; Zambrano, J.G.; Orantes, A.)
Abstract	Vector quantization is a method, used in the lossy compression of voice and images, which can produce results very near to the theoretical limits; however, its principal disadvantage is that the process of search based its functioning on an algorithm of total search, generating a slow process and of a complexity computacional considerable. The present work proposes the combination of two algorithms in the creation of a new vector quantization scheme. First, an associative network is obtained applying a Learning Algorithm for Multivariate Data Analysis (LAMDA) to a codebook generated by means of the LBG algorithm, the purpose of this network is to establish a relation between the training set and the codebook generated by the LBG algorithm; this associative network is a new codebook (LAMDA-codebook) used by the scheme proposed in this work (VQ-LAMDA). Second, considering the LAMDA-codebook as the central element, we use the classification phase of the LAMDA methodology to obtain a rapid search process; the function of this process is generate the set of the class indexes to which every input vector belongs, completing the vector quantization. Furthermore, it is described how to apply the vector quantization scheme proposed to image compression.
Starting Page	743
Ending Page	746
File Size	680080
Page Count	4
File Format	PDF
ISBN	9781424444793
ISSN	15483746
DOI	10.1109/MWSCAS.2009.5235988
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-02
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Image coding Data analysis Artificial neural networks Associative memory Entropy Clustering algorithms Image storage Data compression Neural networks image compression LAMDA methodology evolutionary learning LBG algorithm
Content Type	Text
Resource Type	Article
Subject	Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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
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