Single-frame image super-resolution using learned wavelet coefficients

Jiji, C. V. ; Joshi, M. V. ; Chaudhuri, Subhasis (2004) Single-frame image super-resolution using learned wavelet coefficients International Journal of Imaging Systems and Technology, 14 (3). pp. 105-112. ISSN 0899-9457

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We propose a single-frame, learning-based super-resolution restoration technique by using the wavelet domain to define a constraint on the solution. Wavelet coefficients at finer scales of the unknown high-resolution image are learned from a set of high-resolution training images and the learned image in the wavelet domain is used for further regularization while super-resolving the picture. We use an appropriate smoothness prior with discontinuity preservation in addition to the wavelet-based constraint to estimate the super-resolved image. The smoothness term ensures the spatial correlation among the pixels, whereas the learning term chooses the best edges from the training set. Because this amounts to extrapolating the high-frequency components, the proposed method does not suffer from oversmoothing effects. The results demonstrate the effectiveness of the proposed approach.

Item Type:Article
Source:Copyright of this article belongs to John Wiley and Sons, Inc.
Keywords:Super-resolution; Wavelet decomposition; Regularization; Image restoration
ID Code:7798
Deposited On:25 Oct 2010 10:24
Last Modified:05 Feb 2011 09:12

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