Open AccessNew Access to Improve Super Resolution using Convolution Neural Network
Author(s) -
Rahul Bhattacharya,
K. Parvathi
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1033.0886s19
Subject(s) - computer science , artificial neural network , preprocessor , smoothness , artificial intelligence , convolution (computer science) , pixel , filtration (mathematics) , image (mathematics) , resolution (logic) , pattern recognition (psychology) , computer vision , algorithm , mathematics , statistics , mathematical analysis
Super Resolution is the process to enhance image quality by increasing the pixel densities from a low resolution image. Several methods are proposed in the last few decades. We survey several methods like filtration method i.e. Scalar Smoothness Index filtration, learning based method using Convolution Neural Network. We also propose a new algorithm where we use filtration technique as a preprocessing technique of learning based method.