遥感图像去噪方法研究综述OA北大核心CSTPCD

The complexity of the imaging environment results in remote sensing images containing many types of noise,and the removal of these noises can effectively improve the efficiency and accuracy of the subsequent work.In recent years,image denoising methods for remote sensing have gradually become a hotspot in the field of image processing.On the basis of absorbing the research of many scholars at home and abroad,the denoising methods for visible remote sens-ing images,infrared remote sensing images and SAR images are systematically summarized.Firstly,the main sources and manifestations of noise in remote sensing images are introduced.Secondly,public datasets and data platforms that can be used for the study of remote sensing image denoising methods are listed.The advantages and limitations of traditional remote sensing image denoising methods are described according to the processing domain.Then,the cutting-edge image denoising method for remote sensing based on deep learning is highlighted,and its main innovations and shortcomings are summarized.Finally,the challenges and future development directions of remote sensing image denoising task are ana-lyzed and prospected.