• R. Gokulakrishnan
• Dr. G. Zayaraz
• DR S. Ravi
• R. Bhavya

The recent phenomenal interest in learning-based image super-resolution creates opportunities for the researchers to select the single image super-resolution (SR) for their study as this field has its potential. The response of the researchers has been immense and in the last few years, there are too many research works which motivated us to go for a comprehensive survey on learning-based image super-resolution using sparse representation model. This paper provides a survey on the SR literature in the context of sparse representation. The focus is on the learning based image super resolution using sparse representation. The detailed analysis of the individual work is described in terms of its merits, demerits and accuracy.

Sparse Representation, Super Resolution, Discrete Wavelet Transform, Bayesian Method

"Learning-Based Image Super-Resolution Using Sparse Representation Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.631-635, March-2019, Available :http://www.jetir.org/papers/JETIR1903093.pdf

"Learning-Based Image Super-Resolution Using Sparse Representation Model ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp631-635, March-2019, Available at : http://www.jetir.org/papers/JETIR1903093.pdf