Robust Real-Time Super-Resolution on FPGA and an Application to Video Enhancement
ACM Transactions on Reconfigurable Technology and Systems (TRETS)
A Superresolution Framework for High-Accuracy Multiview Reconstruction
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Structured least squares problems and robust estimators
IEEE Transactions on Signal Processing
Image reconstruction from phased-array MRI data based on multichannel blind deconvolution
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Enhancement of coupled multichannel images using sparsity constraints
IEEE Transactions on Image Processing
Bayesian blind deconvolution from differently exposed image pairs
IEEE Transactions on Image Processing
Video deblurring and super-resolution technique for multiple moving objects
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
Local object-based super-resolution mosaicing from low-resolution video
Signal Processing
The Non-parametric Sub-pixel Local Point Spread Function Estimation Is a Well Posed Problem
International Journal of Computer Vision
A Super-Resolution Framework for High-Accuracy Multiview Reconstruction
International Journal of Computer Vision
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This paper presents a new approach to the blind deconvolution and superresolution problem of multiple degraded low-resolution frames of the original scene. We do not assume any prior information about the shape of degradation blurs. The proposed approach consists of building a regularized energy function and minimizing it with respect to the original image and blurs, where regularization is carried out in both the image and blur domains. The image regularization based on variational principles maintains stable performance under severe noise corruption. The blur regularization guarantees consistency of the solution by exploiting differences among the acquired low-resolution images. Several experiments on synthetic and real data illustrate the robustness and utilization of the proposed technique in real applications.