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Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes
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README.md

Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes
S. Alireza Golestaneh, and Lina J. Karam
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Jul 2017

In this work, we propose a novel effective approach to address the blur detection problem from a single image without requiring any knowledge about the blur type, level, or camera settings. Our approach computes blur detection maps based on a novel High-frequency multiscale Fusion and Sort Transform (HiFST) of gradient magnitudes.

@inproceedings{golestaneh2017spatially,
  title={Spatially-Varying Blur Detection Based on Multiscale Fused and Sorted Transform Coefficients of Gradient Magnitudes},
  author={Golestaneh, S Alireza and Karam, Lina J},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2017}
}
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