ML Anthology

Image Partial Blur Detection and Classification

Renting Liu, Zhaorong Li, Jiaya Jia
CVPR 2008
doi:10.1109/CVPR.2008.4587465 /cvpr/2008/liu2008cvpr-image-a/

Abstract

In this paper, we propose a partially-blurred-image classi fication and analysis framework for automatically detecting images containing blurred regions and recognizing the blur types for those regions without needing to perform blur kernel estimation and image deblurring. We develop several blur features modeled by image color, gradient, and spectrum information, and use feature parameter training to robustly classify blurred images. Our blur detection is based on image patches, making region-wise training and classi-fication in one image efficient. Extensive experiments show that our method works satisfactorily on challenging image data, which establishes a technical foundation for solving several computer vision problems, such as motion analysis and image restoration, using the blur information. ©2008 IEEE.

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Cite

Text

Liu et al. "Image Partial Blur Detection and Classification." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008. doi:10.1109/CVPR.2008.4587465

Markdown

[Liu et al. "Image Partial Blur Detection and Classification." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2008.](https://mlanthology.org/cvpr/2008/liu2008cvpr-image-a/) doi:10.1109/CVPR.2008.4587465

BibTeX

@inproceedings{liu2008cvpr-image-a,
  title     = {{Image Partial Blur Detection and Classification}},
  author    = {Liu, Renting and Li, Zhaorong and Jia, Jiaya},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2008},
  doi       = {10.1109/CVPR.2008.4587465},
  url       = {https://mlanthology.org/cvpr/2008/liu2008cvpr-image-a/}
}