In this study, we propose a deconvolution algorithm based on a modified likelihood model of beamformed intensities (M-DCV) for estimation of the spatial ...

The resulting acoustic intensity images are typically corrupted by signal-dependent noise from Gaussian random field fluctuations arising from the central limit ...

Apr 6, 2024 · In this study, we propose a deconvolution algorithm based on a modified likelihood model of beamformed intensities (M-DCV) for estimation of the ...

In this study, we propose a deconvolution algorithm based on a modified likelihood model of beamformed intensities (M-DCV) for estimation of the spatial ...

Maximum Likelihood Deconvolution of Beamformed Images with Signal-Dependent Speckle Fluctuations from Gaussian Random Fields: With Application to Ocean Acoustic ...

This work proposes a method originated from computer vision deblurring based on deep learning to enhance the spatial resolution of beamformed images by ...

Here, we use the maximum likelihood method to deconvolve the intensity distribution measured on a coherent line array assuming a discrete angular distribution ...

Maximum Likelihood Deconvolution of Beamforming Images with Signal-Dependent Speckle Fluctuations. Authors. Zheng, Yuchen; Ping, Xiaobin; Li, Lingxuan; Wang ...

Aug 23, 2016 · The resulting acoustic intensity images are typically corrupted by signal-dependent noise from Gaussian random field fluctuations arising from ...

Am. 130, 84, 2011. Deconvolution of Beamformed Images with Sigal-Dependent Noise from Gaussian Field Fluctuations. Ankita D. Jain and Nicholas C. Makris ...