Aperture synthesis using a forward-looking ring array is an area of current interest in intracardiac imaging [1]. In
general, data from multiple transmits are coherently combined to implement the synthesis, and schemes for the
specification of the transmit and receive array weightings of the component beams are required. Often schemes
originating in narrowband imaging are applied to broadband, pulse-echo imaging, but the result is usually sidelobes that are very different from those of the narrowband scheme and a rotationally asymmetric two-way response. Beam
asymmetry is a potential disadvantage since the orientation of the array with respect to strong sidelobe reflectors may not be controllable. In the present work, we look for pulse-echo aperture synthesis approaches that produce rotationally symmetric PSFs with low sidelobe levels. Such rotational asymmetry can be decreased by minimizing the maximum delay used in a broadband scheme, and we introduce the idea that this minimization can be accomplished by the combination of delays with phase inversions. We also consider the use of more elements, structured as two rings, in order to increase the number of degrees of freedom available in a small number of transmits. The latter approach allows the design of the desired rotationally symmetric PSFs, which also have much lower peak sidelobe levels than alternative schemes. The proposed scheme makes use of two transmissions per look direction of the dual-ring array. Simulations of planar imaging of spherical voids are presented to illustrate the potential contrast improvement of this approach.
A novel technique for imaging spectroscopy is introduced. The technique makes use of an optical imaging system with a segmented aperture and intensity detector array on the imaging plane. The point spread function (PSF) of such a system can be adjusted by modifying the path lengths from the subapertures to the image plane, and the shape of the resulting point spread function will vary as a function of wavenumber. An image reconstruction approach is taken to convert multiple recorded pan-chromatic images with different wavenumber-varying point spread functions into a hyperspectral data set. Thus, the technique described here is a new form of computed imaging.
KEYWORDS: Point spread functions, Lawrencium, Image sensors, Sensors, Imaging systems, Super resolution, Spatial frequencies, Optical transfer functions, Image acquisition, Signal to noise ratio
Optical imaging systems are often limited in resolution, not by the imaging optics, but by the light intensity sensors on the image formation plane. When the sensor size is larger than the optical spot size, the effect is to smooth the image with a rectangular convolving kernel with one sample at each non-overlapping kernel position, resulting in aliasing. In some such imaging systems, there is the possibility of collecting multiple images of the same scene. The process of reconstructing a de-aliased high-resolution image from multiple images of this kind is referred to as “super-resolution image reconstruction.” We apply the POCS method to this problem in the frequency domain. Generally, frequency domain methods have been used when component images were related by subpixel shifts only, because rotations of a sampled image do not correspond to a simple operation in the frequency domain. This algorithm is structured to accommodate rotations of the source relative to the imaging device, which we believe helps in producing a well-conditioned image synthesis problem. A finely sampled test image is repeatedly resampled to align with each observed image. Once aligned, the test and observed images are readily related in the frequency domain and a projection operation is defined.
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