Sparse sound field decomposition for super-resolution in recording and reproduction.
Koyama, S., N. Murata, and H. Saruwatari.
Journal of the Acoustical Society of America 143, no. 6 (2018): 3780–3795.
Résumé: © 2018 Author(s). A sound field recording and reproduction method based on sparse sound field decomposition is proposed. Most current methods are based on plane-wave or harmonic decomposition of the pressure distribution obtained by microphones, which leads to spatial aliasing artifacts with severe effects. This paper proposes a method for sound field decomposition based on a generative model of the sound field consisting of near-field source components and far-field plane-wave components. Since the distribution of the near-field source components can be assumed to be spatially sparse, the pressure distribution obtained by the microphones can be decomposed into these two components using sparse decomposition algorithms. Using the proposed method, the sound field can be more accurately interpolated and super-resolution in recording and reproduction can be achieved. Experimental results show that the reproduction accuracy above the spatial Nyquist frequency determined by the microphone intervals was improved compared with that of the current methods.
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Adaptive Spatiotemporal SVD Clutter Filtering for Ultrafast Doppler Imaging Using Similarity of Spatial Singular Vectors.
Baranger, J., B. Arnal, F. Perren, O. Baud, M. Tanter, and C. Demene.
IEEE Transactions on Medical Imaging 37, no. 7 (2018): 1574–1586.
Résumé: © 1982-2012 IEEE. Singular value decomposition of ultrafast imaging ultrasonic data sets has recently been shown to build a vector basis far more adapted to the discrimination of tissue and blood flow than the classical Fourier basis, improving by large factor clutter filtering and blood flow estimation. However, the question of optimally estimating the boundary between the tissue subspace and the blood flow subspace remained unanswered. Here, we introduce an efficient estimator for automatic thresholding of subspaces and compare it to an exhaustive list of thirteen estimators that could achieve this task based on the main characteristics of the singular components, namely the singular values, the temporal singular vectors, and the spatial singular vectors. The performance of those fourteen estimators was tested in vitro in a large set of controlled experimental conditions with different tissue motion and flow speeds on a phantom. The estimator based on the degree of resemblance of spatial singular vectors outperformed all others. Apart from solving the thresholding problem, the additional benefit with this estimator was its denoising capabilities, strongly increasing the contrast to noise ratio and lowering the noise floor by at least 5 dB. This confirms that, contrary to conventional clutter filtering techniques that are almost exclusively based on temporal characteristics, efficient clutter filtering of ultrafast Doppler imaging cannot overlook space. Finally, this estimator was applied in vivo on various organs (human brain, kidney, carotid, and thyroid) and showed efficient clutter filtering and noise suppression, improving largely the dynamic range of the obtained ultrafast power Doppler images.
Mots-Clés: Blood flow; Doppler imaging; singular value decomposition; ultrafast imaging; ultrasound
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Compressive acoustic holography with block-sparse regularization.
Fernandez-Grande, E., and L. Daudet.
Journal of the Acoustical Society of America 143, no. 6 (2018): 3737–3746.
Résumé: © 2018 Acoustical Society of America. Sparse reconstruction methods, such as Compressive Sensing, are powerful methods in acoustic array processing, as they make wideband reconstruction possible. However, when addressing sound fields that are not necessarily sparse (e.g., in acoustic near-fields, reflective environments, extended sources, etc.), the methods can lead to a poor reconstruction of the sound field. This study examines the use of sparse analysis priors to promote block-sparse solutions. In particular, a Fused Total Generalized Variation (F-TGV) method is developed, to analyze the sound field in the near-field of acoustic sources. The method promotes sparsity both on the spatial derivatives of the solution and on the solution itself, thus seeking solutions where the non-zero coefficients are grouped together. The performance of the method is examined numerically and experimentally, and compared with established methods. The results indicate that the F-TGV method is suitable to examine both compact and spatially extended sources. The method is promising for its generality, robustness to noise, and the capability to provide a wideband reconstruction of sound fields that are not necessarily sparse.
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Polarization Control of Linear Dipole Radiation Using an Optical Nanofiber.
Joos, M., C. Ding, V. Loo, G. Blanquer, E. Giacobino, A. Bramati, V. Krachmalnicoff, and Q. Glorieux.
Physical Review Applied 9, no. 6 (2018).
Résumé: © 2018 American Physical Society. We experimentally demonstrate that a linear dipole is not restricted to emit linearly polarized light, provided that it is embedded in the appropriate nanophotonic environment. We observe emission of various elliptical polarizations by a linear dipole, including circularly polarized light, without the need for birefringent components. We further show that the emitted state of polarization can theoretically span the entire Poincaré sphere. The experimental demonstration is based on elongated gold nanoparticles (nanorods) deposited on an optical nanofiber and excited by a free-space laser beam. The light directly collected in the guided mode of the nanofiber is analyzed in regard to the azimuthal position and orientation of the nanorods, observed by means of scanning electron microscopy. We demonstrate a mapping between purely geometrical degrees of freedom of a light source and all polarization states that could open the way to alternative methods for polarization control of light sources at the nanoscale.
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