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Super-resolution refers to the process of creating a higher-resolution image with finer details, by utilizing the information of a single low-resolution image or multiple low-resolution ones taken from almost the same scene. Single-frame super-resolution is essentially a task of interpolating between the pixels in the original single-frame image. After a comprehensive bibliographic study of the existing super-resolution techniques, several of the most efficient of these techniques are selected. Also a new implementation, based on a tree data structure is presented.

Produktbeschreibung
Super-resolution refers to the process of creating a higher-resolution image with finer details, by utilizing the information of a single low-resolution image or multiple low-resolution ones taken from almost the same scene. Single-frame super-resolution is essentially a task of interpolating between the pixels in the original single-frame image. After a comprehensive bibliographic study of the existing super-resolution techniques, several of the most efficient of these techniques are selected. Also a new implementation, based on a tree data structure is presented.
Autorenporträt
Izadpanahi, Shima
Dr. Shima Izadpanahi received her M.S. and Ph.D from Computer Engineering Department of Eastern Mediterranean University, North Cyprus. She was then employed as a full-time instructor in Computer Engineering Department of Middle East Technical University. Her current research interests include Super Resolution and Face Image Classification.