Title
A two-phase hybrid codebook generation technique for vector quantization
Abstract
In general, the codebook generation for vector quantization emphasizes two major topics: minimizing the distortion error to improve the quality of the reconstructed image and reducing the time cost to enhance the efficiency. LBG is one of the famous codebook generation techniques proposed in recent decades. LBG was widely utilized due to its simplicity. However, it only guarantees a local optimum. To be an alternative to LBG, the pair-wise nearest neighbor (PNN) algorithm was devised to obtain better results. By the fully searching operation, PNN needs a large amount of calculations. In this paper, a Two-Phase Codebook Generation (TPCG) technique based on the relative pixel magnitudes is presented. With the pre-process of image decomposition, TPCG applies a simple quantifier to divide low frequency blocks in linear time, and then employs a new proposed k-nearest neighbor graph construction approach with Double Linked Algorithm instead of PNN for high frequency blocks. The experiments reveal that TPCG has accuracy approximates to that of PNN while keeping a low time cost.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652473
ICIP
Keywords
Field
DocType
k-nearest neighbors,image quality,image coding,image decomposition,pair-wise nearest neighbor,vector quantization,distortion,time cost reduction,vector quantisation,image reconstruction,k-d tree,double linked algorithm,two-phase hybrid codebook generation,tpcg technique,k-nearest neighbor graph,graph theory,frequency block,pixel magnitude,k-nearest neighbor graph construction,distortion error,pnn algorithm,nearest neighbor,high frequency,merging,low frequency,linear time,pixel,k nearest neighbor,decoding,k d tree,k nearest neighbors,clustering algorithms
k-nearest neighbors algorithm,Pattern recognition,Linde–Buzo–Gray algorithm,Computer science,Local optimum,Image quality,Vector quantization,Artificial intelligence,Time complexity,Distortion,Codebook
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Chia-Chen Yen1315.71
Chih-Ya Shen210317.13
Ming Chen365071277.71