Expeditious Video Super Resolution Using Convolutional Neural Network

Advancements in deep learning techniques have paved a way for efficient up scaling of images and videos. Similar to up scaling an image, we can reach upto a higher resolution by the process of video super resolution. Various existing methods and technologies for achieving a higher resolution are briefly surveyed in this paper and compared to analyze the downfall of the existing approach and proposing a solution. It was ascertained that deep learning approach of Convolutional Neural Network (CNN) is favorable solution to carry out video super resolution. It was also noted that most of the existing techniques focused on either of accuracy or on decreasing complexity, wherein the question of audio was also neglected. Considering the audio factor a innovative video embellished technique is recommended to overcome the balance needed in precision and complexity.