Evaluation of image-shift measurement algorithms for solar Shack-Hartmann wavefront sensors

Löfdahl, Mats G.

doi:10.1051/0004-6361/201015331

Cited by 41 publications

(41 citation statements)

References 15 publications

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“…We find, however that the Fourier-based algorithm strongly underestimates large shifts values. This agrees with results by Löfdahl (2010). For our purpose -(1) no adaptive optics correction, i.e.…”

Section: Simulation Resultssupporting

confidence: 90%

“…I = I − I and R = R − R , where denotes averaging over the N c × N c pixels. w 2 is a 2-dimensional Hamming window as recommended by Löfdahl (2010):…”

Section: Simulation Resultsmentioning

confidence: 99%

“…For r 0 = 5 cm, θ = 3.4 = 7 pixels, hence [−6, +6] pixels is a sufficiently large interval even under strong atmospheric turbulence. The computation of the squared difference is computationally slow, but yields better results than other crosscorrelation algorithms -especially in the regime of large shifts values, see Löfdahl (2010). The precision is further improved to 0.1 pixel by a 2-dimensional quadratic interpolation:…”

Section: Image Analysismentioning

confidence: 99%

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Profiles of the daytime atmospheric turbulence above Big Bear solar observatory

Kellerer

Gorceix

Mariño

et al. 2012

A&A

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Context. Space weather has become acutely critical for today's global communication networks. To understand its driving forces we need to observe the Sun with high angular-resolution, and within large fields-of-view, i.e. with multi-conjugate adaptive optics correction. Aims. The design of a multi-conjugate adaptive optical system requires the knowledge of the altitude distribution of atmospheric turbulence. We have therefore measured daytime turbulence profiles above the New Solar Telescope (NST), on Big Bear Lake. Methods. To this purpose, a wide-field wavefront sensor was installed behind the NST. The variation of the wavefront distortions with angular direction allows the reconstruction of the distribution of turbulence. Results. The turbulence is found to have three origins: 1. a ground layer (<500 m) that contains 55-65% of the turbulence, 2. a boundary layer between 1-7 km comprises 30-40% of the turbulent energy, 3. and the remaining ∼5% are generated in the tropopause, which is above 12 km in summer and between 8 and 12 km in winter. Conclusions. A multi-conjugate adaptive optical system should thus aim at correcting the ground turbulence, the center of the boundary layer at roughly 3 km altitude and, eventually, the upper boundary layer around 6 km altitude.

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Section: Simulation Resultssupporting

confidence: 90%

“…I = I − I and R = R − R , where denotes averaging over the N c × N c pixels. w 2 is a 2-dimensional Hamming window as recommended by Löfdahl (2010):…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Image Analysismentioning

confidence: 99%

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Profiles of the daytime atmospheric turbulence above Big Bear solar observatory

Kellerer

Gorceix

Mariño

et al. 2012

A&A

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“…More recently, Löfdahl (2010) discussed image-shift measurements in the context of solar wavefront sensors, which are also applicable to the LCT implementations.…”

Section: Introductionmentioning

confidence: 99%

Horizontal flow fields observed in Hinode G-band images

Verma

Denker

2011

A&A

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Context. The interaction of plasma motions and magnetic fields is an important mechanism, which drives the solar activity in all its facets. For example, photospheric flows are responsible for the advection of magnetic flux, the redistribution of flux during the decay of sunspots, and the build-up of magnetic shear in flaring active regions. Aims. Systematic studies based on G-band data from the Japanese Hinode mission provide the means to gather statistical properties of horizontal flow fields. This facilitates comparative studies of solar features, e.g., G-band bright points, magnetic knots, pores, and sunspots at various stages of evolution and in distinct magnetic environments, which advances our understanding of the dynamic Sun. Methods. We adapted local correlation tracking (LCT) to measure horizontal flow fields based on G-band images obtained with the Solar Optical Telescope on board Hinode. A total of about 200 time-series with a duration between 1-16 h and a cadence between 15-90 s were analyzed. Selecting a high-cadence (Δt = 15 s) as well as a long-duration (ΔT = 16 h) time-series enabled us to optimize and validate the LCT input parameters, which ensures a robust, reliable, uniform, and accurate processing of a huge data volume. Results. The LCT algorithm produces best results for G-band images with a cadence of 60-90 s. If the cadence is lower, the velocity of slowly moving features will not be reliably detected. If the cadence is higher, the scene on the Sun will have evolved too much to bear any resemblance with the earlier situation. Consequently, in both instances horizontal proper motions are underestimated. The most reliable and yet detailed flow maps are produced using a Gaussian kernel with a size of 2560 km × 2560 km and a full-width-athalf-maximum (FWHM) of 1200 km (corresponding to the size of a typical granule) as sampling window. Conclusions. Horizontal flow maps and graphics for visualizing the properties of photospheric flow fields are typical examples for value-added data products, which can be extracted from solar databases. The results of this study will be made available within the "small projects" section of the German Astrophysical Virtual Observatory (GAVO).

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“…There is no point-like object for wavefront sensing, which is usually performed with a Shack-Hartmann sensor. Instead, the cross correlation between images observed in individual sub-apertures has to be calculated to estimate the shape of the wavefront (Löfdahl, 2010). Significantly poorer daytime atmospheric conditions place much higher demands on the updating frequency of a deformable mirror.…”

Section: Introductionmentioning

confidence: 99%

Review of Image Quality Measures for Solar Imaging

2017

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Observations of the solar photosphere from the ground encounter significant problems caused by Earth's turbulent atmosphere. Before image reconstruction techniques can be applied, the frames obtained in the most favorable atmospheric conditions (the socalled lucky frames) have to be carefully selected. However, estimating the quality of images containing complex photospheric structures is not a trivial task, and the standard routines applied in nighttime lucky imaging observations are not applicable. In this paper we evaluate 36 methods dedicated to the assessment of image quality, which were presented in the literature over the past 40 years. We compare their effectiveness on simulated solar observations of both active regions and granulation patches, using reference data obtained by the Solar Optical Telescope on the Hinode satellite. To create images that are affected by a known degree of atmospheric degradation, we employed the random wave vector method, which faithfully models all the seeing characteristics. The results provide useful information about the method performances, depending on the average seeing conditions expressed by the ratio of the telescope's aperture to the Fried parameter, D/r 0 . The comparison identifies three methods for consideration by observers: Helmli and Scherer's mean, the median filter gradient similarity, and the discrete cosine transform energy ratio. While the first method requires less computational effort and can be used effectively in virtually any atmospheric conditions, the second method shows its superiority at good seeing (D/r 0 < 4). The third method should mainly be considered for the post-processing of strongly blurred images.

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Evaluation of image-shift measurement algorithms for solar Shack-Hartmann wavefront sensors

Cited by 41 publications

References 15 publications

Profiles of the daytime atmospheric turbulence above Big Bear solar observatory

Profiles of the daytime atmospheric turbulence above Big Bear solar observatory

Horizontal flow fields observed in Hinode G-band images

Review of Image Quality Measures for Solar Imaging

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