Image magnification based on a blockwise adaptive Markov random field model
Image and Vision Computing
Edge-and-corner preserving regularization for image interpolation and reconstruction
Image and Vision Computing
Neighbor embedding based super-resolution algorithm through edge detection and feature selection
Pattern Recognition Letters
Simultaneous estimation of super-resolved depth map and intensity field using photometric cue
Computer Vision and Image Understanding
Resolution enhancement based on learning the sparse association of image patches
Pattern Recognition Letters
Fast MAP-based multiframe super-resolution image reconstruction
Image and Vision Computing
A fully automatic one-scan adaptive zooming algorithm for color images
Signal Processing
Performance of reconstruction-based super-resolution with regularization
Journal of Visual Communication and Image Representation
Range map superresolution-inpainting, and reconstruction from sparse data
Computer Vision and Image Understanding
Morphable model space based face super-resolution reconstruction and recognition
Image and Vision Computing
Example-based single image enhanced up-sampling
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
An automatic image scaling up algorithm
MCPR'12 Proceedings of the 4th Mexican conference on Pattern Recognition
A survey of face hallucination
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
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Accurate image expansion is important in many areas of image analysis. Common methods of expansion, such as linear and spline techniques, tend to smooth the image data at edge regions. This paper introduces a method for nonlinear image expansion which preserves the discontinuities of the original image, producing an expanded image with improved definition. The maximum a posteriori (MAP) estimation techniques that are proposed for noise-free and noisy images result in the optimization of convex functionals. The expanded images produced from these methods will be shown to be aesthetically and quantitatively superior to images expanded by the standard methods of replication, linear interpolation, and cubic B-spline expansion