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Image interpolation using shearlet based sparsity priors

: Lakshman, H.; Lim, W.-Q.; Schwarz, H.; Marpe, D.; Kutyniok, G.; Wiegand, T.


IEEE Signal Processing Society; Institute of Electrical and Electronics Engineers -IEEE-:
20th IEEE International Conference on Image Processing, ICIP 2013. Proceedings : 15-18 September 2013, Melbourne, Australia
Piscataway, NJ: IEEE, 2013
ISBN: 978-1-4799-2341-0
International Conference on Image Processing (ICIP) <20, 2013, Melbourne>
Fraunhofer HHI ()

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through thresholding and (c) extracting high frequency information from the approximation and adding it to the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multi-scale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective as well as subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.7 dB is observed over a dataset of 200 images.