• R. Jayasri
• S. Ravi
• R. Shreya

Face detection and recognition is a challenging problem in the area of image processing, computer vision, signal processing and pattern recognition. In the field of face recognition, the sparse representation is the best approach to solve the problem because it is more robustness to deviation in directions, lighting and human expressions in face recognition super resolution. Sparse representation is also called as sparse approximation approach which performs with sparse solutions for systems of linear equations. In this paper, the various methods and techniques involved in sparse representation approach are emphasized with respect to super resolution by providing the detailed analysis on the advantages and disadvantages of face recognition using sparse representation approaches used for super resolution images.

sparse representation, face recognition, super resolution

"Face Image Super-Resolution Algorithms using Sparse Representation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.163-168, April-2019, Available :http://www.jetir.org/papers/JETIR1904F31.pdf

"Face Image Super-Resolution Algorithms using Sparse Representation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp163-168, April-2019, Available at : http://www.jetir.org/papers/JETIR1904F31.pdf