Iterative Single-Image Digital Super-Resolution Using Partial High-Resolution Data

—The subject of extracting high-resolution data from low-resolution images is one of the most important digital processing applications in recent years, attracting much research. In this work the authors show how to improve the resolution of an image when a small part of the image is given in high-resolution. To obtain this result the authors use an iterative procedure imposing the low frequencies complete data of the original low-resolution image and the high-resolution data present only in a fraction of the image. The result is a clearer image, with higher correlation to the required high-resolution image. The authors show the use of such a procedure on Rosetta images to demonstrate the higher frequencies obtained and on a text sample to show improvement in textual understanding.

• Type: Conference
• Year: 2007
• Where: WCE
• Authors: Eran Gur, Zeev Zalevsky
• Keywords: Frequencies Complete Data, Low-resolution Image, Original Low-resolution Image, WCE 2007, WCE 2008