Algorithm About Fog Image Dehazing Based on Transmittance Estimation Model and Guided Filtering

In order to solve the problem of serious degradation of image acquisition equipment under the condition of fog, a fog image defogging algorithm is proposed in this paper presents. Fog weather imaging model was simplified and 2 key variables (light transmittance and atmospheric transmittance value) in the image restoration function was found. We analyzed the influence factors on refractive index as well as the statistics of image gray distribution and a fast estimation algorithm of the model combined with the transmittance was put forward. This algorithm is utilized to estimate atmospheric light by guiding filtering and perform the processing of fog fog image by simplifying repair function. Compared with the HE algorithm (HE Kaiming, SUN Jian, TANG Xiaoou. Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2011, 33:2341) the image after recovery by this defogging algorithm can improve 0.060 4 bit / pixel by using the measure method information entropy, and improve 0.009 55 by using the measure of the standard minimum average gradient. The experimental results show that the proposed algorithm has a better effect on the restoration of the fog image, and the recovery of the details. The effect of defogging is significant.