Single image dehazing method based on detail recovery

Abstract

The present disclosure relates to the field of computer vision image dehazing and discloses a single image dehazing method based on detail recovery. The method includes step 1: constructing a training dataset; step 2: constructing a backbone dehazing network to achieve preliminary image dehazing: based on the U-Net network model, introduce a residual module based on pixel attention mechanism in the encoding region, and an feature enhancement module in the decoding area; step 3: constructing a detail recovery network for image detail recovery, and introducing residual shrinkage module and spatial attention mechanism; step 4: training an overall network model composed of the backbone dehazing network and the detail recovery network; step 5: Testing. The present disclosure can effectively remove fog while improving the problem of edge detail information loss, reducing the blurring of the edges of the dehazing image, and generating a higher-quality dehazing image.