Speckle imaging

About: Speckle imaging is a research topic. Over the lifetime, 3730 publications have been published within this topic receiving 62354 citations.

Near-IR bispectrum speckle interferometry, AO imaging polarimetry, and radiative transfer modeling of the proto-planetary nebula Frosty Leonis

Abstract: Aims. We combined bispectrum speckle interferometry, adaptive optics (AO) imaging polarimetry, and radiative transfer modeling of polarized light to derive various physical properties of the proto-planetary nebula Frosty Leo. Methods. We performed bispectrum K � -band speckle interferometry and H -a ndK-band imaging polarimetry of Frosty Leo using the ESO 3.6 m telescope and the AO-equipped CIAO instrument of the 8 m Subaru telescope, respectively. Two-dimensional radiative transfer modeling was carried out in order to obtain a quantitative interpretation of our observations. Results. Our diffraction-limited speckle image shows distinct hourglass-shaped, point-symmetric bipolar lobes, an equatorial dust lane, and complex clumpy structures in the lobes. Our polarimetric data display a centro-symmetric polarization vector pattern with P ∼ 30–50% in the bipolar lobes and a polarization disk between them. The polarization images also reveal an elongated region with low polarization along a position angle of −45 ◦ . The observations suggest that this region has a low dust density and was carved out by a jet-like outflow. Our radiative transfer modeling can simultaneously explain the observed spectral energy distribution, the intensity distribution of the hourglass-shaped lobes, and our polarization images if we use two grain species with sizes of 0.005 ≤ a ≤ 2.0 μm at latitudes between −2 ◦ and +2 ◦ ,a nd 0.005 ≤ a ≤ 0.7 μm in the bipolar lobes. Assuming a distance of 3 kpc, an expansion velocity of 25 km s −1 , and a gas-to-dust mass ratio of 160, we derive a dust mass of the disk of 2.85 × 10 −3 M� , a gas mass-loss rate of ) ( ) ( *

Measurement-diverse speckle imaging

Abstract: A method and apparatus for obtaining fine resolution imaging of extended objects in the presence of unknown time-varying aberrations, wherein the method is accomplished by obtaining data corresponding to multiple, measurement-diverse images of the extended object collected for each of a plurality of aberration realizations. The object and unknown aberrations are then Jointly estimated, preferably using constrained likelihood-based estimation techniques. The apparatus utilizes a conventional optical system, at least two detector arrays for detecting a plurality of phase-diverse images, a shutter system so that a specklegram can be captured at each of the phase-diverse arrays for each of a plurality of aberration realizations, and a computer including a processor, sufficient memory restoring the digital data corresponding to the captured images, and logic for estimating the object and unknown aberrations.

Application of two oriented partial differential equation filtering models on speckle fringes with poor quality and their numerically fast algorithms.

Abstract: In this paper, we are concerned with denoising in experimentally obtained electronic speckle pattern interferometry (ESPI) speckle fringe patterns with poor quality. We extend the application of two existing oriented partial differential equation (PDE) filters, including the second-order single oriented PDE filter and the double oriented PDE filter, to two experimentally obtained ESPI speckle fringe patterns with very poor quality, and compare them with other efficient filtering methods, including the adaptive weighted filter, the improved nonlinear complex diffusion PDE, and the windowed Fourier transform method. All of the five filters have been illustrated to be efficient denoising methods through previous comparative analyses in published papers. The experimental results have demonstrated that the two oriented PDE models are applicable to low-quality ESPI speckle fringe patterns. Then for solving the main shortcoming of the two oriented PDE models, we develop the numerically fast algorithms based on Gauss–Seidel strategy for the two oriented PDE models. The proposed numerical algorithms are capable of accelerating the convergence greatly, and perform significantly better in terms of computational efficiency. Our numerically fast algorithms are extended automatically to some other PDE filtering models.