May 8, 2023 · In this paper, we propose a novel deep conditional diffusion model under a variational inference framework to solve the AT correction problem.
Atmospheric Turbulence (AT) correction is a challenging restoration task as it consists of two distortions: geometric distortion and spatially variant blur.
Atmospheric Turbulence (AT) correction is a challenging restoration task as it consists of two distortions: geometric distortion and spatially variant blur.
In this paper, we propose a novel deep conditional diffusion model under a variational inference framework to solve the AT correction problem. We use this ...
Sep 8, 2024 · This paper presents a novel variational deep-learning approach for video atmospheric turbulence correction.
Sep 18, 2024 · ABSTRACT This paper presents a novel variational deep-learning approach for video atmospheric turbulence correction.
A technique to perform atmospheric compensation of ground-based telescopes using self-referenced interferometry with a binary holographic recording medium is ...
Missing: Diffusion. | Show results with:Diffusion.
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Jul 26, 2023 · In this paper, we propose a novel deep conditional diffusion model under a variational inference framework to solve the AT correction problem.
This paper presents a novel variational deep-learning approach for video atmospheric turbulence correction. We modify and tailor a Nonlinear Activation Free ...
Missing: Diffusion. | Show results with:Diffusion.
This paper proposes a novel deep conditional diffusion model under a variational inference framework to solve the AT correction problem and uses this ...