The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we propose a new learning-based approach for super resolution image reconstruction utilizing total variation regularization method. By using the total variation (TV) regularization decomposition, we obtain the structure component which consists of edge component and the texture component which does not include edge component of the image. We use the texture component for the learning-based...
Super resolution is not only a key word in active research but also has become a sale point for the recent consumer product such as HDTV. Among a lot of proposals for super resolution image reconstruction, the total variation regularization (TV) method seems to be the most successful approach with sharp edge preservation and no artifacts. The TV regularization method still has two problems. One is...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.