Title :
A new model for daytime visibility index estimation fused average sobel gradient and dark channel ratio
Author :
Wenshu Xiang ; Jianli Xiao ; Chongjing Wang ; Yuncai Liu
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
In this paper, a new fusion model for daytime visibility index estimation using traffic monitoring cameras is proposed, which does not depend on any preset targets or an accurate geometric calibration. In the proposed method, two features Average Sobel Gradient and Dark Channel Ratio are extracted from the input image to construct a visibility range estimation model, and the visibility index is computed based on it. A sunny detector and the gray-scale histogram duration verifications are adopted to improve the accuracy of the model. For evaluating the performance of the proposed method, some experiments have been performed. Experimental results show that the proposed method achieves higher accuracy than other two compared methods.
Keywords :
calibration; cameras; estimation theory; feature extraction; gradient methods; image colour analysis; image fusion; dark channel ratio; daytime visibility index estimation fused average Sobel gradient; geometric calibration; gray-scale histogram duration verification; input image extraction; sunny detector; traffic monitoring camera; Accuracy; Atmospheric modeling; Cameras; Computational modeling; Estimation; Histograms; Indexes; average Sobel gradient; dark channel prior; fusion model; visibility index estimation;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on
Conference_Location :
Dalian
DOI :
10.1109/ICCSNT.2013.6967074