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SAR-to-Optical Image Translation via an Interpretable Network
by
Zhang, Mingjin
, Zhang, Peng
, Zhang, Yuhan
, Yang, Minghai
, Li, Xiaofeng
, Yang, Luchang
, Dong, Xiaogang
in
Artificial intelligence
/ Comparative analysis
/ data collection
/ Deep learning
/ Design
/ Energy conservation law
/ equations
/ first law of thermodynamics-guided branch
/ geometry
/ heat
/ humans
/ Image processing
/ Image quality
/ Methods
/ Neural networks
/ Ordinary differential equations
/ Partial differential equations
/ Remote sensing
/ SAR-to-optical image translation
/ Synthetic aperture radar
/ Technology application
/ Thermodynamics
/ thermodynamics-inspired network
/ third-order finite difference residual structure
/ Translation
/ Visual perception
2024
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SAR-to-Optical Image Translation via an Interpretable Network
by
Zhang, Mingjin
, Zhang, Peng
, Zhang, Yuhan
, Yang, Minghai
, Li, Xiaofeng
, Yang, Luchang
, Dong, Xiaogang
in
Artificial intelligence
/ Comparative analysis
/ data collection
/ Deep learning
/ Design
/ Energy conservation law
/ equations
/ first law of thermodynamics-guided branch
/ geometry
/ heat
/ humans
/ Image processing
/ Image quality
/ Methods
/ Neural networks
/ Ordinary differential equations
/ Partial differential equations
/ Remote sensing
/ SAR-to-optical image translation
/ Synthetic aperture radar
/ Technology application
/ Thermodynamics
/ thermodynamics-inspired network
/ third-order finite difference residual structure
/ Translation
/ Visual perception
2024
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Do you wish to request the book?
SAR-to-Optical Image Translation via an Interpretable Network
by
Zhang, Mingjin
, Zhang, Peng
, Zhang, Yuhan
, Yang, Minghai
, Li, Xiaofeng
, Yang, Luchang
, Dong, Xiaogang
in
Artificial intelligence
/ Comparative analysis
/ data collection
/ Deep learning
/ Design
/ Energy conservation law
/ equations
/ first law of thermodynamics-guided branch
/ geometry
/ heat
/ humans
/ Image processing
/ Image quality
/ Methods
/ Neural networks
/ Ordinary differential equations
/ Partial differential equations
/ Remote sensing
/ SAR-to-optical image translation
/ Synthetic aperture radar
/ Technology application
/ Thermodynamics
/ thermodynamics-inspired network
/ third-order finite difference residual structure
/ Translation
/ Visual perception
2024
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SAR-to-Optical Image Translation via an Interpretable Network
Journal Article
SAR-to-Optical Image Translation via an Interpretable Network
2024
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Overview
Synthetic aperture radar (SAR) is prevalent in the remote sensing field but is difficult to interpret by human visual perception. Recently, SAR-to-optical (S2O) image conversion methods have provided a prospective solution. However, since there is a substantial domain difference between optical and SAR images, they suffer from low image quality and geometric distortion in the produced optical images. Motivated by the analogy between pixels during the S2O image translation and molecules in a heat field, a thermodynamics-inspired network for SAR-to-optical image translation (S2O-TDN) is proposed in this paper. Specifically, we design a third-order finite difference (TFD) residual structure in light of the TFD equation of thermodynamics, which allows us to efficiently extract inter-domain invariant features and facilitate the learning of nonlinear translation mapping. In addition, we exploit the first law of thermodynamics (FLT) to devise an FLT-guided branch that promotes the state transition of the feature values from an unstable diffusion state to a stable one, aiming to regularize the feature diffusion and preserve image structures during S2O image translation. S2O-TDN follows an explicit design principle derived from thermodynamic theory and enjoys the advantage of explainability. Experiments on the public SEN1-2 dataset show the advantages of the proposed S2O-TDN over the current methods with more delicate textures and higher quantitative results.
Publisher
MDPI AG
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