Foggy Image Enhancement Algorithm Based onBidirectional Diffusion and Shock Filtering
摘要
The image obtained by the traditional dark channel prior image defogging fog method is dark and the quality is not high.To solve this problem,a telegraph equation model containing bidirectional diffusion and adaptive shock filtering is established.The edge detector is combined with impulse filtering and the weight coefficient is adaptively selected from the gradient feature of the image to form the sharpening term,so that the image can be enhanced adaptively according to the characteristics of different regions.Adding fidelity items to ensure that the enhanced image preserves the main features of the original image and prevents distortion of the image.On this basis,the finite difference method is used to solve the model numerically to obtain the enhanced image.Experimental results on foggy images show that,compared with the defogging algorithm based on dark channel prior theory and the enhancement algorithm based on adaptive impulse filtering,the proposed algorithm has obvious visual enhancement effect,which can improve the image brightness,reduce the noise effect and improve the image quality.