Title: Directionally adaptive single frame image super resolution

Authors: A.P. Reji, Tessamma Thomas

Addresses: Department of Electronics, Cochin University of Science and Technology, Cochin-22, India. ' Department of Electronics, Cochin University of Science and Technology, Cochin-22, India

Abstract: The single image super resolution recovers missing high resolution details so as to reconstruct a high resolution image from a single low resolution image. This paper proposes a novel directionally adaptive, learning-based, single image super resolution method using multiple direction wavelet transform, called directionlets. Here, critically sampled directionlets are used to capture directional features effectively and to extract edge information along different directions from a set of available high resolution images. This information is used as the training set for super resolving a low resolution input image. The directionlet coefficients at finer scales of its high resolution image are learned locally from this training set and the inverse directionlet transform recovers the super resolved high resolution image. The simulation results showed that the proposed directionlet approach outperforms standard interpolation techniques like cubic spline interpolation as well as standard wavelet-based learning, both visually and in terms of the mean squared error (MSE) values. The SNR scores for cubic spline interpolation, wavelet and directionlet method are 13.6998 dB, 23.8324 dB and 30.8654 dB respectively for Barbara.

Keywords: directionlets; anisotropic; single frame image; super resolution; directionally adaptive; learning; multiple direction wavelet transform; edge information; feature capture; simulation; directional features; information extraction.

DOI: 10.1504/IJICA.2011.041912

International Journal of Innovative Computing and Applications, 2011 Vol.3 No.3, pp.117 - 125

Received: 16 Aug 2010
Accepted: 12 Dec 2010
Published online: 21 Mar 2015 *

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