Image defogging algorithm is widely used in outdoor intelligent monitoring and traffic navigation fields. After defogging， the image clarity is improved to enhance the recognition effect of the target. Dark channel and its improved algorithm have errors in transmittance estimation in bright gray areas such as sky， and are prone to distortion and blurred image details， which will affect image recognition in intelligent transportation field. An adaptive transmittance defogging method is proposed to compensate the transmissivity. Logarithmic transformation is used to obtain logarithmic compensation operator to adjust the transmissivity in the depth of field area. The confidence of dark channel is calculated according to the richness of image information， and the texture compensation operator is constructed combining the image texture information. It can effectively improve the image distortion after defogging. Compared with other defogging algorithms， the proposed algorithm has improved the average gradient， signal-to-noise ratio （SNR）， information entropy and other objective indicators. The image quality has been effectively improved with good transmission compensation effect for the gray bright area， clear and natural image details and moderate brightness.