Blind blur assessment for vision-based applications
| Autor: | Zhongkang Lu, Susu Yao, Shoulie Xie, Shiqian Wu, Weisi Lin, Ee Ping Ong |
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| Rok vydání: | 2009 |
| Předmět: |
Point spread function
Radon transform Image quality business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Edge detection Computer Science::Computer Vision and Pattern Recognition Signal Processing Media Technology Image scaling Point (geometry) Computer vision Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering business Image restoration Mathematics Line Spread Function |
| Zdroj: | Journal of Visual Communication and Image Representation. 20:231-241 |
| ISSN: | 1047-3203 |
| DOI: | 10.1016/j.jvcir.2009.03.002 |
| Popis: | In this paper, a criterion for objective defocus blur measurement is theoretically derived from one image. The essential idea is to estimate the point spread function (PSF) from the line spread function (LSF), whereas the LSF is constructed from edge information. It is proven that an edge point corresponds to the local maximal gradient in a blurred image, and therefore edges can be extracted from blurred images by conventional edge detectors. To achieve high accuracy, local Radon transform is implemented and a number of LSFs are extracted from each edge. The experimental results on a variety of synthetic and real blurred images validate the proposed method. The algorithm can be implemented for image quality evaluation in vision-based applications as no reference images are needed. |
| Databáze: | OpenAIRE |
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