SAR-fused visible light remote sensing image defogging method

Abstract

The invention provides an SAR-fused visible light remote sensing image defogging method, which specifically comprises the following steps of: step 1, selecting SAR images and optical remote sensing images in the same region in the same time period so as to construct an optical-SAR remote sensing image defogging data set, and dividing the data set into a training set and a verification set; step 2,constructing a conditional generative adversarial convolutional neural network as a defogging model, wherein the model is composed of a generative network and a discrimination network; step 3, jointly training the defogging model; and step 4, defogging a visible light remote sensing image by using the trained defogging model. According to the SAR-fused visible light remote sensing image defoggingmethod, the mapping relation between a foggy image and a clear image is directly learned through using the conditional generative adversarial network, and end-to-end defogging can be achieved; SAR information is fused, and defogging visual enhancement is achieved; and a cascaded residual expansion convolution block structure is adopted, so that supervised learning can be performed on the defogging model, and efficient defogging can be realized.

Description

technical field [0001] The invention relates to a method for defogging a visible light remote sensing image by integrating SAR (aperture radar), and belongs to the technical field of remote sensing image processing. Background technique [0002] Optical remote sensing images can not only provide rich ground object information, but also have spectral characteristics, which play a very important role in the fields of environment, monitoring, military, surveying and mapping. However, optical remote sensing images are often disturbed by fog, resulting in blurred objects in the image and loss of information in regions of interest. This not only seriously affects the interpretation of image data by human eyes, but also affects the automatic interpretation of remote sensing data. [0003] Dehazing research on remote sensing images can improve image quality, thus providing guarantee for subsequent remote sensing image processing and applications. Many dehazing methods for remote se...

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