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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Research on Quality Improvement of Polarization Imaging in Foggy Conditions
verfasst von : Congli Li, Wenjun Lu, Song Xue, Yongchang Shi
Erschienen in: Intelligence Science and Big Data Engineering
Verlag: Springer Berlin Heidelberg
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A new method was presented to improve quality of polarization imaging in foggy weather. In this method, two state-of-art algorithms were used to defog three polarization direction images by polarization imaging. Then Stokes parameter representation was used to parse polarization parameter images. Further image quality assessment based on natural scene statistics was used to verify the acquired polarization parameter images. Sampling images of different foggy density were used in validation experiments. The images were acquired by polarization parameters measurement platform in simulation environment of haze and fog. Subjective and objective assessments show that this method can effectively enhance quality of polarization imaging in foggy conditions. It is easy to be implemented and expanded, and has adaptability to the changes of fog density.