Single image defogging algorithm based on attention mechanism

Aiming at the problem that the existing defogging algorithm is not ideal for defogging, a single image defogging algorithm based on attention mechanism is proposed. Channel attention and pixel attention are constructed by introducing attention mechanism, and the feature attention module is realized by combining the two. Then the basic module is built through multi-scale convolution, local residual learning, and feature attention. At last, the end-to-end defogging is realized by global residual learning. The experimental results show that the algorithm is superior to the comparison algorithm in three image evaluation indexes of peak signal-to-noise ratio(PSNR), structural similarity(SSIM) and feature similarity(FSIM), and it achieves a good defogging effect and effectively solves the problems of undesirable defogging effect