Image partial blur detection and classification

• Published in: 2008 IEEE Conference on Computer Vision and Pattern Recognition pp. 1 - 8
• Main Authors: Renting Liu, Zhaorong Li, Jiaya Jia
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2008
• Subjects: Computer science; Data mining; Image analysis; Image color analysis; Image restoration; Image segmentation; Information analysis; Kernel; Motion analysis; Motion detection
• ISBN: 9781424422425; 1424422426
• ISSN: 1063-6919
• DOI: 10.1109/CVPR.2008.4587465

In this paper, we propose a partially-blurred-image classification 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 classification 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.