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A Bayesian approach for high resolution imaging of small changes in multiple scattering media
Fan Xie1, Ludovic Moreau2, Yuxiang Zhang2
1Institute of Geophysics, China Earthquake Administration, 10086 Beijing, China.
Ultrasonics
|September 6, 2015
Summary
This study presents a Bayesian imaging method for high-resolution detection of sub-wavelength changes, even with multiple scattering. The novel approach utilizes a Monte Carlo Markov Chain algorithm for improved accuracy in complex media.
Area of Science:
- Physics
- Applied Mathematics
- Imaging Science
Background:
- Multiple scattering complicates high-resolution imaging.
- Detecting sub-wavelength changes requires advanced inversion techniques.
Purpose of the Study:
- To introduce a Bayesian approach for high-resolution imaging of sub-wavelength changes.
- To address challenges posed by multiple scattering in imaging.
Main Methods:
- Bayesian inference combined with a Monte Carlo Markov Chain (MCMC) algorithm.
- Minimization of a cost function based on waveform decorrelations.
- Incorporation of an analytical model for the medium's sensitivity kernel.
Main Results:
- Successful high-resolution imaging of sub-wavelength changes.
- Demonstrated effectiveness in the presence of multiple scattering.
- Validation through numerical and experimental examples, outperforming linear inversion.
Conclusions:
- The proposed Bayesian method offers superior performance for sub-wavelength imaging.
- The approach is robust and validated for complex scattering environments.
- This technique advances the capabilities of imaging methods like Locadiff.
