Title
Context-Constrained Hallucination For Image Super-Resolution
Abstract
This paper proposes a context-constrained hallucination approach for image super-resolution. Through building a training set of high-resolution/low- resolution image segment pairs, the high-resolution pixel is hallucinated from its texturally similar segments which are retrieved from the training set by texture similarity. Given the discrete hallucinated examples, a continuous energy function is designed to enforce the fidelity of high-resolution image to low-resolution input and the constraints imposed by the hallucinated examples and the edge smoothness prior. The re-constructed high-resolution image is sharp with minimal artifacts both along the edges and in the textural regions. ©2010 IEEE.
Publication Date
8-31-2010
Publication Title
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Number of Pages
231-238
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CVPR.2010.5540206
Copyright Status
Unknown
Socpus ID
77956006189 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77956006189
STARS Citation
Sun, Jian; Zhu, Jiejie; and Tappen, Marshall F., "Context-Constrained Hallucination For Image Super-Resolution" (2010). Scopus Export 2010-2014. 1029.
https://stars.library.ucf.edu/scopus2010/1029