• Surya Prasasda Rao Borra
• Geetha Devi Appari
• Balaji Tata

In many surveillance video applications, it is of interest to recognize an object or a person, which occupies a small portion of a Low-Resolution [LR], noisy video. Hence to enhance the Image quality and the resolution of the Image, Super Resolution [SR] Image Reconstruction Algorithm is used. An efficient Image Super Resolution [SR] methodology using Principal Component Analysis [PCA] is applied to obtain a High Resolution [HR] image from a set of low resolution video frames. The Super Resolution [SR] methodology involves mainly four basic steps such as Registration, Fusion, Interpolation, and Restoration. In this project, the Low Resolution [LR] images are registered by using Scale Invariant Feature Transform method. The registered images are fused by using Principal Component Analysis method.

Low Resolution, Super Resolution, Interpolation, Registration, Principal Component Analysis

"PRINCIPAL COMPONENT ANALYSIS BASED SUPER RESOLUTION RECONSTRUCTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.577-582, November-2018, Available :http://www.jetir.org/papers/JETIR1811982.pdf

"PRINCIPAL COMPONENT ANALYSIS BASED SUPER RESOLUTION RECONSTRUCTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp577-582, November-2018, Available at : http://www.jetir.org/papers/JETIR1811982.pdf