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Found 4 papers, 1 papers with code
Estimation of non-uniform blur using a patch-based regression convolutional neural network (CNN)
The non-uniform blur of atmospheric turbulence can be modeled as a superposition of linear motion blur kernels at a patch level.
Neural-based Compression Scheme for Solar Image Data
In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs.
Estimation of motion blur kernel parameters using regression convolutional neural networks
Many deblurring and blur kernel estimation methods use a maximum a posteriori (MAP) approach or deep learning-based classification techniques to sharpen an image and/or predict the blur kernel.
Solar Active Region Magnetogram Image Dataset for Studies of Space Weather
In this dataset we provide a comprehensive collection of magnetograms (images quantifying the strength of the magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO).
