This paper proposes a Kalman filter based restoration method for images obtained by in-vehicle camera in foggy conditions. The proposed method introduces two novel approaches into the Kalman filter based restoration. The first one is an automatic determination of a fog deterioration model. A vanishing point in the foggy image is estimated by using cross ratio of lane marking, and automatic determination of all parameters of the fog deterioration model is realized. Furthermore, the obtained model is introduced into the Kalman filter. Specifically, our method regards each frame as a state variable and its observation model is defined by the fog deterioration model. Then, since the correlation between successive frame can be effectively utilized by the Kalman filter, the accurate restoration of foggy images is achieved. Experimental results show that the proposed method achieves higher performance than the traditional method based on the fog deterioration model.
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Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Date of Conference: March 31 2008-April 4 2008