CFP last date

by
Krisshnamoorthy R,
Punidha R

International Journal of Computer Applications |

Foundation of Computer Science (FCS), NY, USA |

Volume 47 - Number 6 |

Year of Publication: 2012 |

Authors: Krisshnamoorthy R, Punidha R |

10.5120/7193-9954 |

Krisshnamoorthy R, Punidha R . Fast vector Quantization of Color Image Coding with Single Codebook based on Orthogonal Polynomials. International Journal of Computer Applications. 47, 6 ( June 2012), 19-25. DOI=10.5120/7193-9954

@article{
10.5120/7193-9954,

author = {
Krisshnamoorthy R,
Punidha R
},

title = { Fast vector Quantization of Color Image Coding with Single Codebook based on Orthogonal Polynomials },

journal = {
International Journal of Computer Applications
},

issue_date = { June 2012 },

volume = { 47 },

number = { 6 },

month = { June },

year = { 2012 },

issn = { 0975-8887 },

pages = {
19-25
},

numpages = {9},

url = {
https://ijcaonline.org/archives/volume47/number6/7193-9954/
},

doi = { 10.5120/7193-9954 },

publisher = {Foundation of Computer Science (FCS), NY, USA},

address = {New York, USA}

}

%0 Journal Article

%1 2024-02-06T20:41:11.896451+05:30

%A Krisshnamoorthy R

%A Punidha R

%T Fast vector Quantization of Color Image Coding with Single Codebook based on Orthogonal Polynomials

%J International Journal of Computer Applications

%@ 0975-8887

%V 47

%N 6

%P 19-25

%D 2012

%I Foundation of Computer Science (FCS), NY, USA

In this paper, a new fast vector quantization encoding technique for transform coding of RGB color images that does not require a color coordinate conversion matrix is proposed. The proposed work directly applies the orthogonal polynomials transformation on the input image and transformed training set with reduced dimension is obtained for the vector quantization and hence the proposed work has reduced computational complexity. In the codebook generation phase of vector quantization encoding, a new transformed binary tree algorithm is proposed to construct a single codebook for all the three color components, utilizing the inter-correlation property of the individual color plane as well as interactions among the color planes with the proposed transformation and so a big saving in codebook construction time is achieved. A new transformed tree structured codeword matching algorithm is proposed in order to further reduce the vector quantization encoding time for finding the closest codeword of an input vector. The experimental results show that the proposed algorithm greatly reduces the encoding time when compared with recent fast vector quantization algorithms.

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