Single Frame Image Super Resolution Using Learned Directionlets

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Single Frame Image Super Resolution Using Learned Directionlets

Show simple item record Tessamma, Thomas Reji, A P 2014-08-12T09:23:27Z 2014-08-12T09:23:27Z 2010-10
dc.description International Journal of Artificial Intelligence & Applications (IJAIA), Vol.1, No.4, October 2010 en_US
dc.description.abstract In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. This method uses directionlets to effectively capture directional features and to extract edge information along different directions of a set of available high resolution images .This information is used as the training set for super resolving a low resolution input image and 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 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. This method gives good result with aliased images also. en_US
dc.description.sponsorship Cochin University of Science and Technology en_US
dc.language.iso en en_US
dc.subject Directionlet en_US
dc.subject anisotropic en_US
dc.subject super resolution en_US
dc.title Single Frame Image Super Resolution Using Learned Directionlets en_US
dc.type Article en_US

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