Chen Chen — Publications

C. Chen, and J. E. Fowler, “Single-Image Super-Resolution Using Multihypothesis Prediction,” in Proceedings of the 46th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2012, pp. 608-612. [Code] [BibTeX]
  • Abstract:
    Single-image super-resolution driven by multihypothesis prediction is considered. The proposed strategy exploits self-similarities existing between image patches within a single image. Specifically, each patch of a low-resolution image is represented as a linear combination of spatially surrounding hypothesis patches. The coefficients of this representation are calculated using Tikhonov regularization and then used to generate a high-resolution image. Experimental results reveal that the proposed algorithm offers significantly higher-quality super-resolution than bicubic interpolation without the cost of training on an extensive training set of imagery as is typical of competing single-image techniques.

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