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Blur Feature Extraction Plus Automatic KNN Matting: A Novel Two Stage Blur Region Detection Method for Local Motion Blurred Images
- Source :
- IEEE Access, Vol 7, Pp 181142-181151 (2019)
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- To deal with the serious visual artifacts caused by the consistent restoration algorithm on local motion blurred images, a novel two stage blur region detection method including coarse location and region refinement for local blurred images is proposed in this paper. First, blur feature discriminant criteria in frequency domain and spatial domain is defined to generate blur feature image; then, binarization is used on the blur feature image to obtain the coarse blur region detection map; subsequently, morphological methods are used to process the clear and blur areas and the trimap is obtained. Finally, the refinement detection of blur region is achieved by combination of the trimap and automatic KNN matting algorithm. Experimental results show that the proposed algorithm can detect the local blurred region quickly and effectively, and it has outperformed other traditional methods in the application of blur region detection and image restoration as well.
- Subjects :
- local blur feature
General Computer Science
Computer science
business.industry
Feature extraction
General Engineering
Region detection
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Motion (geometry)
KNN matting
image restoration
Image processing
blur feature extraction
image quality
General Materials Science
Computer vision
Artificial intelligence
Stage (hydrology)
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
lcsh:TK1-9971
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 7
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....b384dd072a0c117676e044e0f2aa8312