Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/77483
Title: Self-sampled image resolution enhancement using dual-tree complex wavelet transform
Authors: Celik, T. 
Kusetogullari, H.
Issue Date: 2009
Citation: Celik, T.,Kusetogullari, H. (2009). Self-sampled image resolution enhancement using dual-tree complex wavelet transform. European Signal Processing Conference : 2017-2021. ScholarBank@NUS Repository.
Abstract: In this paper, a dual-tree complex wavelet transform domain image resolution enhancement method is proposed. The method estimates detail wavelet coefficients for the input low-resolution (LR) image using different types of deformations on the initial estimate of high-resolution (HR) image. Edge preserving smoothing filtering with different parameters is used in deformations. Decomposition of each deformed HR image results in a different set of detail wavelet coefficients for LR image, and the resultant HR image is computed by averaging the different reconstructions from LR image using different detail wavelet coefficient sets. The perceptual and objective quality of resolution enhanced images compare favorably with recently emerged methods in the field. © EURASIP, 2009.
Source Title: European Signal Processing Conference
URI: http://scholarbank.nus.edu.sg/handle/10635/77483
ISSN: 22195491
Appears in Collections:Staff Publications

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