Image interpolation based on non-local geometric similarities and directional gradients
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Sivut | 1707-1719 |
| Sivumäärä | 13 |
| Julkaisu | IEEE Transactions on Multimedia |
| Vuosikerta | 18 |
| Numero | 9 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 1 syyskuuta 2016 |
| OKM-julkaisutyyppi | A1 Alkuperäisartikkeli |
Tiivistelmä
Image interpolation offers an efficient way to compose a high-resolution (HR) image from the observed low-resolution (LR) image. Advanced interpolation techniques design the interpolation weighting coefficients by solving a minimum mean-square-error (MMSE) problem in which the local geometric similarity is often considered. However, using local geometric similarities cannot usually make the MMSE-based interpolation as reliable as expected. To solve this problem, we propose a robust interpolation scheme by using the nonlocal geometric similarities to construct the HR image. In our proposed method, the MMSE-based interpolation weighting coefficients are generated by solving a regularized least squares problem that is built upon a number of dual-reference patches drawn from the given LR image and regularized by the directional gradients of these patches. Experimental results demonstrate that our proposed method offers a remarkable quality improvement as compared to some state-of-the-art methods, both objectively and subjectively.