Research on Ship Recognition Based on Adaptive Image Enhancement and Defogging

An adaptive image enhancement defogging ship recognition method is proposed to detect ships navigating on heavy foggy weather. This method is applicable to different image sources, including gray scale transform from radar echo data and video image captured by cameras. The adaptive image enhancement methend is applied to the acquired foggy image, which includes image preprocessing, logarithmic transformation enhancement, gamma transform enhancement, and the ACE algorithm for fusion defogging. The purpose is to highlight the features of the ship target. The defogged images will be handled by filtering, grey scale transformation and Canny edge detection, and the ship will be recognized using HOG and SVM. The results indicate that the method can not only produce a defogging image, but also recognize the ship more clearly, and does not need a large number of data sets for training. At the same time, the method has a wide range of applicability, faster processing speed, and able to deal with different sources of image data, which provides technical support for the monitoring of ships and safety management.