PurposeIsolating the mainlobe and sidelobe contribution to the ultrasound image can improve imaging contrast by removing off-axis clutter. Previous work achieves this separation of mainlobe and sidelobe contributions based on the covariance of received signals. However, the formation of a covariance matrix at each imaging point can be computationally burdensome and memory intensive for real-time applications. Our work demonstrates that the mainlobe and sidelobe contributions to the ultrasound image can be isolated based on the receive aperture spectrum, greatly reducing computational and memory requirements.ApproachThe separation of mainlobe and sidelobe contributions to the ultrasound image is shown in simulation, in vitro, and in vivo using the aperture spectrum method and multicovariate imaging of subresolution targets (MIST). Contrast, contrast-to-noise-ratio (CNR), and speckle signal-to-noise-ratio are used to compare the aperture spectrum approach with MIST and conventional delay-and-sum (DAS) beamforming.ResultsThe aperture spectrum approach improves contrast by 1.9 to 6.4 dB beyond MIST and 8.9 to 13.5 dB beyond conventional DAS B-mode imaging. However, the aperture spectrum approach yields speckle texture similar to DAS. As a result, the aperture spectrum-based approach has less CNR than MIST but greater CNR than conventional DAS. The CPU implementation of the aperture spectrum-based approach is shown to reduce computation time by a factor of 9 and memory consumption by a factor of 128 for a 128-element transducer.ConclusionsThe mainlobe contribution to the ultrasound image can be isolated based on the receive aperture spectrum, which greatly reduces the computational cost and memory requirement of this approach as compared with MIST.
Imaging spectrometers are frequently used in remote sensing for their increased target discrimination capabilities over conventional imaging. Increasing the spectral resolution of these sensors further enables the system’s ability to discriminate certain targets and adds the potential for monitoring narrow-line spectral features. We describe a high spectral resolution (Δλ=1.1 nm full-width at half maximum) snapshot imaging spectrometer capable of distinguishing two narrowly separated bands in the red-visible spectrum. A theoretical model is provided to detail the first polarization grating-based spatial heterodyning of a Savart plate interferometer. Following this discussion, the experimental conditions of the narrow-line imaging spectrometer (NLIS) are provided. Finally, calibration and target identification methods are applied and quantified. Ultimately it is demonstrated that in a full spectral acquisition the NLIS sensor is capable of less than 3.5% error in reconstruction. Additionally, it is demonstrated that neural networks provide greater than 99% reduction in crosstalk when compared to pseudoinversion and expectation maximization in single target identification.
Polarization spatial heterodyne interferometry (PSHI) allows for the development of compact, vibration insensitive, high spectral resolution sensors. Introducing the imaging qualities of a lenslet array extends the advantages of PSHI to imaging interferometers. The use of Savart plates enables a birefringent interferometer that obtains higher spectral resolution with fewer optical aberrations when compared to alternative designs. In this paper, we describe the design, construction, calibration and validation of a narrowband emission line imaging spectrometer (NELIS), based on Savart plates and liquid crystal polarization gratings, along with its associated theoretical model. This sensor is advantageous for spectral imaging in the areas of remote sensing, biomedical imaging and machine vision.
We show how highly chromatic Multi-Twist Retarder (MTR) films can be used to create a single-film color filter wherein the color may be selected only by the MTR orientation angle. By this approach, we can create multi- color images with just an MTR between polarizers. We study the design method and limits of the available color gamut possibilities in this approach, and experimentally demonstrate several designs of continuous and discrete patterns. This technique may be useful in art, displays, microscopy, and remote sensing.
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