Research of Dehazing Algorithm Based on Dark Channel Prior

Aiming at the problems of block effect and high algorithm complexity in the dark channel prior dehazing algorithm, we propose an improved dehazing algorithm based on the dark channel prior. First, row transmittance is obtained through the dark channel prior dehazing algorithm, and then the haze parameters are adjusted adaptively by the peak signal-to-noise ratio to obtain the optimized transmittance. Then, the above results are trained as the input vector and the target vector of the multilayer perceptron to establish the mapping between the row transmittance and the optimized transmittance and obtain the optimized transmittance. Finally, the image is restored by the atmosphere light value to obtain the haze-free image. Experimental results show that the algorithm can effectively improve the block effect, improve the restoration efficiency, and improve the clarity of image details to a certain extent.