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Yang, Seungjoon
Signal Processing Lab .
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Image interpolation using interpolative classified vector quantization

Author(s)
Hong, Sung-HoPark, Rae-HongYang, SeungjoonKim, Jun-Yong
Issued Date
2008-02
DOI
10.1016/j.imavis.2007.05.002
URI
https://scholarworks.unist.ac.kr/handle/201301/7890
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=35848936704
Citation
IMAGE AND VISION COMPUTING, v.26, no.2, pp.228 - 239
Abstract
According to advances in digital imaging technology, interest in high-resolution (HR) images has been increased. Various methods that convert low-resolution (LR) images to HR ones have been presented. In this paper, to reduce the computational load we propose a vector quantization (VQ) based algorithm that reconstructs an interpolation image by adding to an initially interpolated image high-frequency components predicted from training with a number of example image sets. The proposed interpolative classified VQ (ICVQ) algorithm combines interpolative VQ with classified VQ. With a number of (LR and HR) example image sets, we construct two types of (LR and HR) codebooks. Comparative experiments with three conventional image interpolation algorithms show that the proposed interpolation algorithms using ICVQ effectively preserve edges to which the human visual system is sensitive. The proposed algorithm can be applicable to various image- and video-based applications such as digital camera and digital television.
Publisher
ELSEVIER SCIENCE BV
ISSN
0262-8856
Keyword (Author)
interpolationvector quantizationinterpolative classified vector quantization
Keyword
SUPERRESOLUTIONRECONSTRUCTIONALGORITHM

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