Super-resolution aims to produce a high-resolution image from a set of one or more low-resolution images by recovering or inventing plausible high-frequency image content. Typical...
Lyndsey C. Pickup, Stephen J. Roberts, Andrew Ziss...
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,...
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
This paper investigates the use of the Bayesian inference for devising an example-based rendering procedure. As prior model of this Bayesian inference, we exploit the multiscale n...
In cross-modal inference, we estimate complete fields from noisy and missing observations of one sensory modality using structure found in another sensory modality. This inference...
S. Ravela, Antonio B. Torralba, William T. Freeman