文章基本信息

标题：Single Image Super Resolution Algorithms: A Survey and Evaluation
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作者：Ruaa Adeeb Abdulmunem Al-falluji ; Aliaa Abdel-Halim Youssif ; Shawkat K. Guirguis 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2017
卷号：6
期号：9
页码：1445-1451
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Image processing sub branch that specifically deals with the improvement, of images and videos, resolution without compromising the detail and visual effect but rather enhances the two, is known as Super Resolution. Multiple (multiple input images and one output image) or single (one input and one output) low resolution images are converted to high resolution. Single image super resolution algorithms are more practical since multiple images are not always available. The paper presents a survey of recent single image super resolution methods that are based on the use of external database to predict the values of missing pixels in high resolution image.
关键词：Super resolution; Sparese dictionary; Random forest; Convolution neural network