@inproceedings{286863662c084cf18338a5f37ce8d76b,
title = "Image super resolution reconstruction using iterative adaptive regularization method and genetic algorithm",
abstract = "Super resolution is a technique to obtain high resolution images from several degraded low-resolution images. This has got attention in the research society because of its wide use in many fields of science and technology. Even though many methods exist for super resolution, adaptive regularization method is preferred because of its simplicity and the constraints used to get better image restoration result. In this paper first adaptive algorithm is considered to restore better edge and texture of image. Further Genetic algorithm is used to smooth the noise and better frequency addition into the image to get an optimum super resolution image.",
keywords = "(LR:HR), Genetic algorithm (GA), Low/high Resolution, Peak signal to noise ratio (PSNR), Regularization",
author = "Panda, {S. S.}",
year = "2015",
doi = "10.1007/978-81-322-2208-8_62",
language = "English (US)",
volume = "32",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "675--681",
booktitle = "Computational Intelligence in Data Mining - Proceedings of the International Conference on CIDM",
address = "Germany",
note = "1st International Conference on Computational Intelligence in Data Mining, ICCIDM 2014 ; Conference date: 20-12-2014 Through 21-12-2014",
}