Topic
Spatial filter
About: Spatial filter is a research topic. Over the lifetime, 6170 publications have been published within this topic receiving 100451 citations.
Papers published on a yearly basis
Papers
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TL;DR: The advantages of using an optical cavity and applications ranging from inertial sensors to tests of gravity in quantum mechanics are discussed, and interference fringes are demonstrated using the first atom interferometer in a optical cavity.
Abstract: We propose and demonstrate a new scheme for atom interferometry, using light pulses inside an optical cavity as matter wave beam splitters. The cavity provides power enhancement, spatial filtering, and a precise beam geometry, enabling new techniques such as low power beam splitters ( 75% contrast and measure the acceleration due to gravity, g, to 60 μg/sqrt[Hz] resolution in a Mach-Zehnder geometry. We use >10(7) cesium atoms in the compact mode volume (600 μm 1/e(2) waist) of the cavity and show trapping of atoms in higher transverse modes. This work paves the way toward compact, high sensitivity, multiaxis interferometry.
83 citations
TL;DR: A novel scheme to optimize the focusing condition for real-time, swept-source optical coherence microscopy by exploiting the axial and lateral behaviors of four-zone binary-phase spatial filters is reported.
Abstract: We report a novel scheme to optimize the focusing condition for real-time, swept-source optical coherence microscopy. The axial and lateral behaviors of four-zone binary-phase spatial filters are presented numerically. A nearly constant axial intensity distribution along an extended depth of focus of 1.5 mm and a lateral resolution of 5 μm are experimentally verified. The A-line scan rate is up to 16 kHz, yielding a frame rate of 25 Hz and 640 lines per image.
83 citations
TL;DR: The triple objective of designing a spatial/spectral classifier is considered, which is compact (uses as few features as possible), discriminative (enhances class separation), and robust (works well in small sample situations).
Abstract: Including spatial information is a key step for successful remote sensing image classification. In particular, when dealing with high spatial resolution, if local variability is strongly reduced by spatial filtering, the classification performance results are boosted. In this paper, we consider the triple objective of designing a spatial/spectral classifier, which is compact (uses as few features as possible), discriminative (enhances class separation), and robust (works well in small sample situations). We achieve this triple objective by discovering the relevant features in the (possibly infinite) space of spatial filters by optimizing a margin-maximization criterion. Instead of imposing a filter bank with predefined filter types and parameters, we let the model figure out which set of filters is optimal for class separation. To do so, we randomly generate spatial filter banks and use an active-set criterion to rank the candidate features according to their benefits to margin maximization (and, thus, to generalization) if added to the model. Experiments on multispectral very high spatial resolution (VHR) and hyperspectral VHR data show that the proposed algorithm, which is sparse and linear, finds discriminative features and achieves at least the same performances as models using a large filter bank defined in advance by prior knowledge.
82 citations
TL;DR: Experimental filtering results for a Gaussian input function, which is modulated by an additive chirp noise, are shown and excellent agreement between experiments and computer simulations is achieved.
Abstract: In the Wigner domain of a one-dimensional function, a certain chirp term represents a rotated line delta function. On the other hand, a fractional Fourier transform (FRT) can be associated with a rotation of the Wigner-distribution function by an angle connected with the FRT order. Thus with the FRT tool a chirp and a delta function can be transformed one into the other. Taking the chirp as additive noise, the FRT is used for filtering the line delta function in the appropriate fractional Fourier domain. Experimental filtering results for a Gaussian input function, which is modulated by an additive chirp noise, are shown. Excellent agreement between experiments and computer simulations is achieved.
82 citations
TL;DR: In this paper, the role of numerical methods to simulate the several physical processes (diffraction, self-focusing, gain saturation) involved in coherent beam propagation through large laser systems is discussed.
Abstract: The evolution of solid-state laser systems over the past decade, both through technological advances and through increased understanding of the interplay between nonlinear effects and linear diffraction, is reviewed. The role of numerical methods to simulate the several physical processes (diffraction, self-focusing, gain saturation) involved in coherent beam propagation through large laser systems is discussed. A comprehensive simulation code for modeling all of the pertinent physical phenomena observed in laser operations (growth of small-scale modulation, spatial filtering, imaging, gain saturation, and beam-induced damage) is described in detail. The realism and accuracy of results obtained with this numerical code stem from an unambiguous identification of the sources of spatial noise, and from the use of spatial filters in modern lasers to limit the transverse beam modulation scale within the practical computational range of a two-dimensional numerical analysis. Several comparisons between code results and solid-state laser output performance data are presented. Finally, the design and performance estimation of the large Nova laser system presently under construction at the Lawrence Livermore National Laboratory (LLNL) are given.
82 citations