A Fast Single-Image Dehazing Method Based on a Physical Model and Gray Projection

Due to the scattering of atmospheric particles, images captured under hazy conditions suffer from contrast attenuation and color distortion, which severely affect the performance of machine vision systems. Various types of methods have been developed to improve the clarity of images. However, these methods are typically challenging to apply in real-time systems. We present a fast, single-image dehazing method based on the atmospheric scattering theory and dark channel prior theory. The transmission map is approximately estimated using a fast average filter, the subsection mechanism is designed to avoid the high brightness of the sky region in the recovered image, the region projection method is adopted to obtain the atmospheric light, and image color compensation is implemented using the Weber-Fechner law. Our experimental results show that this algorithm can restore images to a clear and natural state and ensure the balance of quality and the speed of image restoration. Therefore, the algorithm can be used in real-time systems.