• Devang B Bhatt
• Vishal M Patel

Super Resolution technique is use to reconstruct a High Resolution from Low Resolution Image. Image Super Resolution is process of recovering the missing high frequency detail and removing the degradation that arise. In general, SR approaches can be divide into three categories: Interpolation Based, Reconstruction Based and Example Learning Based. Interpolation based methods are used to predict the missing pixel value on the LR image. The super-resolution image reconstruction can be transform to solve linear equations whose size depends on the number of the training data. When the amount of the training data is large, it is time-consuming to solve the regression problem. To solve this problem select part of pair wise values from training database instead of all the training data. Support Vector Regression (SVR) technique is use to generalize unseen

Super Resolution, Interpolation, Support vector Regression, Image Reconstruction

"A Review: Interpolation Based Super Resolution Approach for Improving Quality of Single Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.250-259, May-2018, Available :http://www.jetir.org/papers/JETIR1805048.pdf

"A Review: Interpolation Based Super Resolution Approach for Improving Quality of Single Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp250-259, May-2018, Available at : http://www.jetir.org/papers/JETIR1805048.pdf