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 current color image super-resolution methods, superresolution based on sparse representation achieves state-of-the-art performance. However, the exploited sparse representation models deal with the color images as independent channel planes. Consequently, these approaches process the color pixels as scalar quantity, lacking of accuracy in describing inter-relationship among color channels. In this...
Single image super-resolution (SR) is a severely unconstrained task. While the self-example-based methods are able to reproduce sharp edges, they perform poorly for textures. For recovering the fine details, higher-level image segmentation and corresponding external texture database are employed in the example-based SR methods, but they involve too much human interaction. In this paper, we discuss...
Recently, the example-based super-resolution method has been extensively studied due to its vivid perception. However, this kind of method directly transfers the high-frequency details of the examples to the low-resolution image, incurring false structures and over-sharpness around the texture regions. In this paper, the problem in the example-based method is investigated from an analytic discussion...
Image super-resolution reconstruction (SR) has drawn a lot of attentions lately. But almost all existing SR algorithms do not consider about the noisy image SR problem. This paper proposes a novel super-resolution algorithm for noisy images based on sparse mixing estimators. Firstly, sparse mixing estimators are introduced to achieve a directional and sparse representation of noisy low resolution...
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.