| abstract |
The invention provides a turbid underwater polarization image restoration method based on a generative adversarial network. Including the following steps: step 1, build an underwater active imaging system, and shoot clear underwater intensity images and turbid underwater polarized images; step 2, establish a data set; divide the data set into a training set according to the ratio of 8:1:1 , validation set, test set; step 3, build a generative network; step 4, pre-training; use the data set in step 2 to pre-train the generative network; step 5, build a discriminant network; step 6, build a generative confrontation network; form a generative adversarial network with the pre-trained generative network in step 4, and use cross-entropy as a loss function to train the generative adversarial network; step 7, use the trained generative adversarial network for image restoration. Compared with the prior art, the present invention can realize the restoration of high turbidity underwater polarized images. |