UHD image dehazing method based on global and local aware networks
Current multilayer perceptron(MLP)-based models usually require flattening pixels on an image and sub-sequently enforce a self-attention mechanism or"Mix"enhancement scheme to achieve global modeling of images and obtain long-range dependence of the image.However,these approaches generally consume considerable computing re-sources to bridge the loss of spatial topological information in image reconstruction.Particularly for UHD image dehaz-ing tasks,numerous stacked MLP models suffer from memory overflow when running a UHD-hazed image on a re-source-constrained device.A novel model for real-time dehazing of 4 K images on a single GPU(110 fps)is proposed here to address this issue.This model is advantageous because it maintains spatial information of the raw image and has low computational complexity.
万方数据
维普
