Spatial stabilization of deep-turbulence-induced anisoplanatic blur

Paxman, Richard G.; Rogne, Timothy J.; Sickmiller, Brett A.; LeMaster, Daniel A.; Miller, Jason J.; Vollweiler, Candice G.

doi:10.1364/oe.24.029109

Cited by 10 publications

(8 citation statements)

References 22 publications

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“…Two recent publications simulated and then demonstrated from experimental data the existence of “spatial stabilization of deep-turbulence-induced anisoplanatic blur.” 19 , 20 The observed spatial stabilization phenomenon means that in deep turbulence-observed PSFs, even in the presence of a very small isoplanatic angle, do not vary radically over small position changes in the image plane. Instead, PSFs with relatively simple structure occur over slightly larger regions, varying with image plane position in a well-correlated manner.…”

Section: Discussionmentioning

confidence: 99%

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Universal dictionaries for representation of turbulent atmosphere point spread functions

2023

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Dictionary methods have proved very useful in compressive sensing. Herein we show that, for dictionaries to represent the point spread functions (PSFs) of image formation in atmospheric turbulence, it is possible to construct dictionaries computationally. Computationally created dictionaries make unnecessary the exhaustive collection of PSF data, for arbitrarily large numbers of conditions of turbulence and optical image formation systems, while also reducing the overall number of dictionaries that need to be created and stored.

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Section: Discussionmentioning

confidence: 99%

“…We also note that the experimental data leading to the verification of the spatial stabilization in Refs. 19 and 20 is from the same data set that was used to compile the results reported in Ref. 2 and used in the tests reported directly above.…”

Section: Discussionmentioning

confidence: 99%

Universal dictionaries for representation of turbulent atmosphere point spread functions

2023

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“…A third imaging scenario is where the camera is elevated, looking down at the ground, and a majority of the turbulent effects occur near the object. 2,3 This case is also anisoplanatic in nature with spatially varying PSFs but to a greater degree than the horizontal imaging case.…”

Section: Collecting Imagery Through Atmospheric Turbulencementioning

confidence: 94%

Scalability conjecture for the Fried parameter in synthesis of turbulent atmosphere point spread functions

Hunt

Iler

Rucci

2018

J. Appl. Rem. Sens.

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Abstract. A common method for synthesizing turbulent imagery is to model phase perturbations on a wavefront and then propagate the wavefront to the entrance pupil of an imaging system. The point spread function (PSF) that results from the wavefront in the pupil is then computed and used to synthesize images by the usual means of convolution. In a recent publication, a method was disclosed using sparse and redundant dictionaries of turbulent characteristics to construct PSFs directly in the image plane and simulate image formation without making phase models and computing wavefront propagation. However, the dictionary method, as disclosed in the recent publication, is limited to modeling PSFs characterized by the Fried parameter of the data used to construct the dictionary. Herein, we demonstrate that a dictionary constructed from data with a given Fried parameter can be scaled to construct turbulent PSFs corresponding to larger and smaller values of the Fried parameter. This enables a single dictionary, or a small number of dictionaries, to serve for the simulation of turbulent images over a range of turbulence conditions. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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“…In spite of imaging via a self-adaptive optical telescope, the anisoplanatic effect is still salient [7,8]. In order to overcome the shortages as mentioned above, Paxman et al [9] proposed a method to simulate the anisoplanatic effect by using a wavefront coding technique. Thereafter, multiple frame superimposition was adopted instead of long-term exposure imaging to reduce the effect of anisoplanatism, and image definition was also improved [10].…”

Section: Introductionmentioning

confidence: 99%

Multiframe Astronomical Image Registration Based on Block Homography Estimation

Luo

2020

Journal of Sensors

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Due to the influence of atmospheric turbulence, a time-variate video of an observed object by using the astronomical telescope drifts randomly with the passing of time. Thereafter, a series of images is obtained snapshotting from the video. In this paper, a method is proposed to improve the quality of astronomical images only through multiframe image registration and superimposition for the first time. In order to overcome the influence of anisoplanatism, a specific image registration algorithm based on multiple local homography transformations is proposed. Superimposing registered images can achieve an image with high definition. As a result, signal-to-noise ratio, contrast-to-noise ratio, and definition are improved significantly.

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Spatial stabilization of deep-turbulence-induced anisoplanatic blur

Cited by 10 publications

References 22 publications

Universal dictionaries for representation of turbulent atmosphere point spread functions

Universal dictionaries for representation of turbulent atmosphere point spread functions

Scalability conjecture for the Fried parameter in synthesis of turbulent atmosphere point spread functions

Multiframe Astronomical Image Registration Based on Block Homography Estimation

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