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Computational Imaging Through Atmospheric Turbulence. Stanley H. Chan, Nicholas Chimitt

Computational Imaging Through Atmospheric Turbulence


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ISBN: 9781638281702 | 250 pages | 7 Mb
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  • Computational Imaging Through Atmospheric Turbulence
  • Stanley H. Chan, Nicholas Chimitt
  • Page: 250
  • Format: pdf, ePub, fb2, mobi
  • ISBN: 9781638281702
  • Publisher: Now Publishers
Download Computational Imaging Through Atmospheric Turbulence

Electronics e-books pdf: Computational Imaging Through Atmospheric Turbulence by Stanley H. Chan, Nicholas Chimitt 9781638281702 (English literature)

Simulating Anisoplanatic Turbulence by Sampling In this paper, we present a propagation-free method for simulating imaging through anisoplanatic atmospheric turbulence. The key innovation that enables  Image Restoration Methods for Imaging through One way to alleviate the degradation caused by atmospheric turbulence is to apply post-processing mitigation algorithms, where a high-quality  Image Reconstruction of Static and Dynamic Scenes Ground based long-range passive imaging systems often suffer from degraded image quality due to a turbulent atmosphere. While methods exist for removing  Real-Time Dense Field Phase-to-Space Simulation of Abstract: Numerical simulation of atmospheric turbulence is one of the biggest bottlenecks in developing computational techniques for  ASF-Transformer: neutralizing the impact of atmospheric Recently, deep learning-based methods have shown promise in image restoration tasks [15–17] and computational imaging [18–20] without using  An imaging-based approach to measure atmospheric turbulence The strength information of atmospheric turbulence is hidden in its infrared imaging effects. We have developed a deep learning method to  A linear systems approach to imaging through turbulence improvements by statistical frame selection for adaptive-optics imaging through atmospheric turbulence. Optical Engineering, 33(10):3254–3264, 1994. [36]  Atmospheric turbulence mitigation for sequences with The moving objects are detected and tracked using the improved Gaussian mixture models (GMM) and Kalman filtering. New fusion rules are 

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