A Prototype System for Atmospheric Visibility Estimation Based on Image Analysis and Learning
Xi Xu · Journal of Information and Computational Science · 2014
Visibility plays an important role in transportation, communication, agriculture, industry and so on. It is also an indication of air quality. This paper presents the design, implementation, and evaluation of a prototype system for estimating visibility quantitatively based on image analysis and learning. Firstly, an image of measured scene including objects and their background was captured by conventional video camera and the image features were extracted from spatial and frequency domain respectively. Secondly, SVR (Support Vector Regression) model was dynamically produced with the training set according to the image. Lastly, visibility of the image was calculated by SVR model with its features as input vector. A ground truth dataset covering the whole range is used to evaluate the performance of the system and the experimental results show that the system has both simple operation and high accuracy, and it is stable enough to be applied for the whole range of visibility in practical applications.