Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line Single-image super-resolution via linear mapping of interpolated self-examples. IEEE Transactions on image processing, 23 (12). pp. 5334-5347. ISSN 1057-7149 (2014)
Full text not available from this repository.Abstract
This paper presents a novel example-based single-image superresolution procedure that upscales to high-resolution (HR) a given low-resolution (LR) input image without relying on an external dictionary of image examples. The dictionary instead is built from the LR input image itself, by generating a double pyramid of recursively scaled, and subsequently interpolated, images, from which self-examples are extracted. The upscaling procedure is multipass, i.e., the output image is constructed by means of gradual increases, and consists in learning special linear mapping functions on this double pyramid, as many as the number of patches in the current image to upscale. More precisely, for each LR patch, similar self-examples are found, and, because of them, a linear function is learned to directly map it into its HR version. Iterative back projection is also employed to ensure consistency at each pass of the procedure. Extensive experiments and comparisons with other state-of-the-art methods, based both on external and internal dictionaries, show that our algorithm can produce visually pleasant upscalings, with sharp edges and well reconstructed details. Moreover, when considering objective metrics, such as Peak signal-to-noise ratio and Structural similarity, our method turns out to give the best performance.
| Item Type: | Article |
|---|---|
| Identification Number: | https://doi.org/10.1109/TIP.2014.2364116 |
| Uncontrolled Keywords: | Super resolution; example-based; neighbor embedding; regression; super resolution |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Ms T. Iannizzi |
| Date Deposited: | 11 Dec 2014 11:38 |
| Last Modified: | 11 Dec 2014 11:38 |
| URI: | http://eprints.imtlucca.it/id/eprint/2417 |
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