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Found 7 papers, 1 papers with code
Compressive Shack-Hartmann Wavefront Sensor based on Deep Neural Networks
However if there exists strong atmospheric turbulence or the brightness of guide stars is low, the accuracy of wavefront measurements will be affected.
Data--driven Image Restoration with Option--driven Learning for Big and Small Astronomical Image Datasets
In recent years, developments of deep neural networks and increments of the number of astronomical images have evoked a lot of data--driven image restoration methods.
PSF--NET: A Non-parametric Point Spread Function Model for Ground Based Optical Telescopes
Assuming point spread functions induced by the atmospheric turbulence with the same profile belong to the same manifold space, we propose a non-parametric point spread function -- PSF-NET.
Point Spread Function Modelling for Wide Field Small Aperture Telescopes with a Denoising Autoencoder
For wide field small aperture telescopes, the point spread function is hard to model, because it is affected by many different effects and has strong temporal and spatial variations.
Solar Image Restoration with the Cycle-GAN Based on Multi-Fractal Properties of Texture Features
Texture is one of the most obvious characteristics in solar images and it is normally described by texture features.
Perception Evaluation -- A new solar image quality metric based on the multi-fractal property of texture features
Next-generation ground-based solar observations require good image quality metrics for post-facto processing techniques.
Optical Transient Object Classification in Wide Field Small Aperture Telescopes with Neural Networks
In this paper, we propose two transient classification methods based on neural networks.
