2results about How to "Improve denoising efficiency" patented technology

The application discloses a deep learning point target denoising method for remote sensing task planning and belongs to the technical field of mega remote sensing constellation task planning.The application is aimed at the problem that the existing method is slow in calculating the satellite imaging time window for a point target in mega remote sensing constellation task planning and is time-consuming.The application comprises the following steps: orbit recursion is carried out according to the initial coordinate position of each satellite to determine the eccentric anomaly and the true anomaly at a given time;the orbit six numbers and the longitude, latitude and height of the task target are expressed as coordinate vectors in the ECEF coordinate system to calculate the imaging side swing angle;the golden section search method is adopted to determine the imaging time window;the imaging time and the imaging side swing angle are compared to determine the mark L and obtain a training data set;the point task denoising neural network is trained by using the network training data set, and the cross-entropy loss function is used for training and fitting of the neural network to obtain the trained point task denoising neural network.The application is used for point target denoising in remote sensing task planning.

The embodiment of the application provides a kind of image denoising method, device, system, edge device and storage medium, the method comprises: obtaining to be denoised image;With preset multi-head attention mechanism module, the first feature matrix of to-be-denosed image is extracted, wherein, preset multi-head attention mechanism module includes self-attention mechanism and channel attention mechanism;First feature matrix is up-sampled, and second feature matrix is obtained;Based on second feature matrix, the denoised image corresponding to to-be-denosed image is generated. The technical scheme provided in the embodiment of the application can improve the image denoising efficiency, reduce the consumption of computing resources, and then reduce the performance requirements of the device.