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Proceedings Paper

Classification and codebook design for a vector quantizer
Author(s): Mahmoud K. Quweider; Ezzatollah Salari
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Paper Abstract

This paper presents a classified vector quantizer based on Peano scanning. The Peano scanning, which is used to reduce the dimensionality of the data provides a 1D algorithm to classify an image block. The class of the block is determined based on its Peano scanning value from a look up table (LUT) of representative Peano scanning values and their associated classes. The Peano scanning algorithm is easily implemented in hardware and the class can be determined in a logarithmic time proportional to the number of entries in the LUT when using a binary search algorithm on the sorted LUT. Moreover, the class look up table is easily implemented in real time. An effective algorithm to generate all the codebooks of the classes simultaneously in a systematic way based on the greedy tree growing algorithm is also presented. The monochromatic images encoded in the range of 0.625 - 0.813 with a 16 dimensional input vectors are shown to preserve the edge integrity and quality as determined by subjective and objective measures.

Paper Details

Date Published: 16 September 1994
PDF: 11 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185979
Show Author Affiliations
Mahmoud K. Quweider, Univ. of Toledo (United States)
Ezzatollah Salari, Univ. of Toledo (United States)


Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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