• Ramya R
• Dr. M.Senthilmurugan

Super-resolution (SR) is the process of combining a sequence of low resolution images in- order to produce a higher resolution images. The goal of super resolution, as its name suggests, is to increase the resolution of an image. Reduction of noise and blur in the super resolution process is a challenge task in reconstruction. Resolution of registered image depends on accurate feature extraction and matching. These factors reduce the quality of the image. In this paper we presented a novel approach for simultaneous image registration, interpolation and restoration is proposed with the help of affine transformation, RANdom SAmple Consensus, New Edge Directed Interpolation and MAP-MRF. The performance of the proposed is verified with quality metrics such as PSNR, SSIM and MSE values with existing methods. The results show that the proposed method generates high quality images

SIFT (Scale Invariant Feature Transform), PCA-SIFT (Principal Component Analysis Scale Invariant Feature Transform), SURF (Speeded up Robust Features), POCS (Projections Onto Convex Sets), RANSAC (RANdom SAmple Consensus) ASIFT (Affine Scale Invariant Feature Transform).

"MAP-MRF based Simultaneous Image Registration, Interpolation and Restoration for Super Resolution Image Reconstruction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 10, page no.368-374, October-2018, Available :http://www.jetir.org/papers/JETIR1810955.pdf

"MAP-MRF based Simultaneous Image Registration, Interpolation and Restoration for Super Resolution Image Reconstruction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 10, page no. pp368-374, October-2018, Available at : http://www.jetir.org/papers/JETIR1810955.pdf