Abstract/Details

An algorithm for image data compression based on vector quantization

Mishra, Sanjay. 
 Texas A&I University ProQuest Dissertations Publishing,  1991. 1343720.

Abstract (summary)

Image data compression is concerned with minimization of the number of information carrying units used to represent an image. Fundamental goal of data compression is to store reduced number of bits or transmit fewer bits. New algorithms for data compression and, consequent image restoration are developed and implemented. Data compression is achieved by actual quantization, or conversion into a fixed or discrete quantities. Two dimensional discrete integral-valued sample of image pixels are continually quantized, until a desired set of codebook vectors is formed. This codebook is then used for image data compression. Thus, data can be either transmitted or stored with reduced bits. It is shown that using the same codebook, image data can be easily restored back to its original form, while maintaining the necessary fidelity of the data.

Indexing (details)


Subject
Computer science
Classification
0984: Computer science
Identifier / keyword
Applied sciences
Title
An algorithm for image data compression based on vector quantization
Author
Mishra, Sanjay
Number of pages
128
Degree date
1991
School code
0510
Source
MAI 29/04M, Masters Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
979-8-208-04104-8
Advisor
Omar, Iqbal
University/institution
Texas A&I University
University location
United States -- Texas
Degree
M.S.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
1343720
ProQuest document ID
303967682
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
https://www.proquest.com/docview/303967682