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Found 7 papers, 1 papers with code
Scattering and Gathering for Spatially Varying Blurs
A spatially varying blur kernel $h(\mathbf{x},\mathbf{u})$ is specified by an input coordinate $\mathbf{u} \in \mathbb{R}^2$ and an output coordinate $\mathbf{x} \in \mathbb{R}^2$.
Real-Time Dense Field Phase-to-Space Simulation of Imaging through Atmospheric Turbulence
We show that the cross-correlation of the Zernike modes has an insignificant contribution to the statistics of the random samples.
Imaging through the Atmosphere using Turbulence Mitigation Transformer
The new data synthesis process enables the generation of large-scale multi-level turbulence and ground truth pairs for training.
Accelerating Atmospheric Turbulence Simulation via Learned Phase-to-Space Transform
Fast and accurate simulation of imaging through atmospheric turbulence is essential for developing turbulence mitigation algorithms.
Image Reconstruction of Static and Dynamic Scenes through Anisoplanatic Turbulence
Ground based long-range passive imaging systems often suffer from degraded image quality due to a turbulent atmosphere.
Simulating Anisoplanatic Turbulence by Sampling Inter-modal and Spatially Correlated Zernike Coefficients
Simulating atmospheric turbulence is an essential task for evaluating turbulence mitigation algorithms and training learning-based methods.
Rethinking Atmospheric Turbulence Mitigation
We demonstrate how a simple prior can outperform state-of-the-art blind deconvolution methods.
