Literature DB >> 29877400

Transport-based model for turbulence-corrupted imagery.

J M Nichols, T H Emerson, L Cattell, S Park, A Kanaev, F Bucholtz, A Watnik, T Doster, G K Rohde.   

Abstract

A new model for turbulence-corrupted imagery is proposed based on the theory of optimal mass transport. By describing the relationship between photon density and the phase of the traveling wave, and combining it with a least action principle, the model suggests a new class of methods for approximately recovering the solution of the photon density flow created by a turbulent atmosphere. Both coherent and incoherent imagery are used to validate and compare the model to other methods typically used to describe this type of data. Given its superior performance in describing experimental data, the new model suggests new algorithms for a variety of atmospheric imaging and wave propagation applications.

Year:  2018        PMID: 29877400     DOI: 10.1364/AO.57.004524

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  2 in total

1.  Radon Cumulative Distribution Transform Subspace Modeling for Image Classification.

Authors:  Mohammad Shifat-E-Rabbi; Xuwang Yin; Abu Hasnat Mohammad Rubaiyat; Shiying Li; Soheil Kolouri; Akram Aldroubi; Jonathan M Nichols; Gustavo K Rohde
Journal:  J Math Imaging Vis       Date:  2021-08-05       Impact factor: 1.627

2.  Parametric Signal Estimation Using the Cumulative Distribution Transform.

Authors:  Abu Hasnat Mohammad Rubaiyat; Kyla M Hallam; Jonathan M Nichols; Meredith N Hutchinson; Shiying Li; Gustavo K Rohde
Journal:  IEEE Trans Signal Process       Date:  2020-05-25       Impact factor: 4.931

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.