Multi-frame compression: theory and design
Signal Processing - Special section on signal processing technologies for short burst wireless communications
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive interpolation of images
Signal Processing
Dictionary learning algorithms for sparse representation
Neural Computation
Regularized Shock Filters and Complex Diffusion
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A comparison of three total variation based texture extraction models
Journal of Visual Communication and Image Representation
A multi-frame image super-resolution method
Signal Processing
A super-resolution reconstruction algorithm for surveillance images
Signal Processing
Image super-resolution via sparse representation
IEEE Transactions on Image Processing
Image Super-Resolution Based on MCA and Wavelet-Domain HMT
IFITA '10 Proceedings of the 2010 International Forum on Information Technology and Applications - Volume 02
Exploiting self-similarities for single frame super-resolution
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
On single image scale-up using sparse-representations
Proceedings of the 7th international conference on Curves and Surfaces
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
New edge-directed interpolation
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
Image decomposition via the combination of sparse representations and a variational approach
IEEE Transactions on Image Processing
A MAP Approach for Joint Motion Estimation, Segmentation, and Super Resolution
IEEE Transactions on Image Processing
A New Orientation-Adaptive Interpolation Method
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Simultaneous image fusion and super-resolution using sparse representation
Information Fusion
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Due to the fact that natural images are inherently sparse in some domains, sparse representation has led to interesting results in image acquiring, representing, and compressing high-dimensional signals. Based on the experiences and learned priors in sparse domain from low and high resolution images, the typical ill-posed inverse problem of image super-resolution is effectively solved by the l"1-norm optimization techniques. However, how to reasonably combine the sparse representation theory and the feature of natural images is still a critical issue for performances improvements of image super-resolution algorithms. Considering the fact that the different morphologic features in natural images should be regularized by different constrains in sparse domain, in this paper we present a novel sparse representation algorithm with reasonable morphologic regularization for single image super-resolution. Extensive experimental results on various natural images validate the superiority of the proposed algorithm in terms of qualitative and quantitative performance.