A Novel Dehazing Network Based on Point-by-Point Attention Enhancement

Under stormy weather conditions, the image quality captured by the imaging equipment is low, showing low image contrast and low scene brightness. The image processed by the non-local algorithm has phenomena such as edge blur in dense fog areas, object edge halo, and color distortion. In order to solve this problem, a new end-to-end defogging network based on attention feature fusion technology is proposed. The proposed network uses the RepVGG-SSE module in the encoding part to enhance features, and uses a point-wise pixel-level attention module to achieve high-dimensional feature enhancement. Extensive experimental results show that this method outperforms most existing defogging methods. This method has a remarkable image defogging effect, which improves image details while reducing the impact of image color distortion.