Optimized Video Super Resolution By Predictive Analytics And Machine Learning

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Dr. Safinaz S , Dr. K Bhanu Rekha


For specific image super-resolution process, HR images are considered by discerning natural image priors and self-similarity enclosed by image and for video super resolution. On the contrary, spatial information through positions and temporal information through frames could be deployed to develop specifics for LR frame. So far numerous research works has been carried out in this region of research and this present research aims to develop an actual hybrid RNN-ACO algorithm for augmenting the video super resolution. To inspect the performance metrics, the research work is carried out in PYTHON tool which displays the accuracy of suggested approach. Deployment of hybrid RNN-ACO model to expand the video super resolution framework will be implemented and the corresponding assessment factors will be analyzed and equated for individual RNN and ACO and collective RNN-ACO model.

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