Spatial-temporal switching estimators for imaging locally concentrated dynamics

• URL: http://arxiv.org/abs/2102.10167v1
• Date: Fri, 19 Feb 2021 21:36:47 GMT
• Title: Spatial-temporal switching estimators for imaging locally concentrated dynamics
• Authors: Parisa Karimi, Mark Butala, Zhizhen Zhao, Farzad Kamalabadi
• Abstract summary: A switching linear dynamic system (SLDS) is a natural model under which to pose such problems. Because of the high parameter space dimensionality, efficient and accurate recovery of the underlying state is challenging. This paper focuses on the common cases where the dynamic evolution may be adequately modeled as a collection of decoupled, locally concentrated dynamic operators.
• Score: 18.73097340265486
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The evolution of images with physics-based dynamics is often spatially localized and nonlinear. A switching linear dynamic system (SLDS) is a natural model under which to pose such problems when the system's evolution randomly switches over the observation interval. Because of the high parameter space dimensionality, efficient and accurate recovery of the underlying state is challenging. The work presented in this paper focuses on the common cases where the dynamic evolution may be adequately modeled as a collection of decoupled, locally concentrated dynamic operators. Patch-based hybrid estimators are proposed for real-time reconstruction of images from noisy measurements given perfect or partial information about the underlying system dynamics. Numerical results demonstrate the effectiveness of the proposed approach for denoising in a realistic data-driven simulation of remotely sensed cloud dynamics.

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