Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2205.13650

Multi-frame blind deconvolution and phase diversity with statistical inclusion of uncorrected high-order modes

Mats G. Löfdahl·Tomas Hillberg
View original source ↗Read source document ↗Export metadata ↓

Abstract

Images collected with ground-based telescopes suffer blurring and distortions from turbulence in Earth's atmosphere. Adaptive optics (AO) can only partially compensate for these effects. Neither multi-frame blind deconvolution (MFBD) nor speckle techniques restore AO-compensated images to the correct power spectrum and contrast. MFBD can only compensate for a finite number of low-order aberrations, leaving a tail of uncorrected high-order modes. Speckle restoration of AO-corrected data depends on calibrations of the AO corrections and assumptions regarding the height distribution of atmospheric turbulence. We seek to develop an improvement to MFBD that combines speckle's usage of turbulence statistics to account for high-order modes with the ability of MFBD to sense low-order modes that can be partially corrected by AO and/or include fixed or slowly changing instrumental aberrations. We modify the image-formation model, supplementing the fitted low-order wavefront aberrations with tails of random high-order aberrations. These tails follow Kolmogorov statistics scaled to estimated or measured values of Fried's parameter, r0, that characterize the strength of the seeing at the moment of data collection. We refer to this as statistical diversity (SD). We test MFBD with SD with noise-free synthetic data, simulating many different r0 and numbers of AO-corrected modes. SD improves the contrasts and power spectra of restored images, both in accuracy and in consistency with varying r0, without penalty in processing time. With focus diversity (FD), the results are almost perfect. SD also reduces errors in the fitted wavefront parameters. MFBD with SD and FD seems resistant to several percents of error in r0. Adding SD to MFBD shows great promise for improving contrasts and power spectra in restored images. Further studies with real data are merited.

Explore related subjects

astro-ph.IMastro-ph.SR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mats G. Löfdahl, Tomas Hillberg. 2022-10-31. Multi-frame blind deconvolution and phase diversity with statistical inclusion of uncorrected high-order modes. https://doi.org/10.1051/0004-6361%2F202244123

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Scale-Vector Alignment: A Scale-Aware Framework for Spatially Resolved Morphological Similarity in Astronomical Images

Astronomical maps made with different tracers are not expected to have identical morphology. Excitation, optical depth, chemistry, radiation, and ISM phase alter the response of a tracer, and the resulting differences can depend on both position and spatial scale. We propose scale-vector alignment, a scale-aware method based on Constrained Diffusion Decomposition (CDD). CDD decomposes an image into localized scale components; at each position, their amplitudes define a scale vector that describes how the measured intensity is distributed over spatial scale. We define the pixel-wise similarity $\Spix(x,y)$ as the normalized alignment of two local scale vectors. The normalization removes the overall amplitude, so $\Spix$ compares relative scale composition rather than absolute flux. We also define the scale-wise similarity $\Sscale(l)$ by comparing the two CDD component maps at each spatial scale. Spatial shifts are used to construct an empirical shifted reference distribution for $\Spix$. In Orion~A, the tracer with the highest similarity to the dust-derived column-density map changes from $^{12}$CO to $^{13}$CO to C$^{18}$O toward higher column density. In NGC~6334I(N), the line--continuum similarity decreases locally around the brightest compact structures, where radiative-transfer effects can alter the observed line morphology. In NGC~3627, CO is most similar to 21~$μ$m emission, and $\Sscale$ reaches its maximum at an intermediate sub-kpc scale. The method measures where two tracers have similar multiscale structure and at which scales their spatial distributions agree. The implementation is publicly available at https://github.com/meng-ke/Scale-Vector-Alignment.

astro-ph.IM↗
arXiv2026

Fast and accurate astronomical source deblending with Density-Peak Clustering

Source deblending is a fundamental challenge for current and forthcoming astronomical surveys, where increasing source density and image depth lead to a growing number of overlapping detections. Accurate deblending is essential for reliable measurements of source morphology and photometry, as well as for cosmological analyses. We present a redesign of the Advanced Density Peak (ADP) clustering algorithm, tailored to the identification and separation of blended astronomical sources within detection regions. We develop a validation framework combining realistic image simulations, automatically generated ground-truth segmentation, and label-invariant metrics. ADP is assessed against ASTErIsM, an established density-based astronomical deblender, using pairwise simulations, synthetic multi-source images, and Euclid Q1 public data. In pairwise simulations, the methods show comparable performance across a broad range of source separations and flux ratios, with photometric differences typically below 1% and reaching 5-7% in the most challenging cases, without systematic bias. In multi-source simulations, ADP recovers approximately 8% more ground-truth sources, while the positions of sources identified by both methods agree at the sub-pixel level. On Euclid Q1 public data, the methods show strong agreement in segmentation area, ellipticity, position angle, and photometry, with the largest differences for the smallest and faintest sources. ADP also provides a substantial computational advantage: end-to-end benchmarks on 19200 x 19200 pixel Euclid images require approximately 16-200 s, corresponding to speedups of 12-156x relative to ASTErIsM, with median and mean improvements of 36x and 54x, respectively. These results show that ADP provides scientifically competitive deblending at substantially lower computational cost, making it a promising approach for large-scale astronomical imaging surveys.

astro-ph.IM↗
arXiv2026

IceCube Upgrade status and perspectives

The IceCube Neutrino Observatory instruments one cubic kilometer of deep-glacial ice between 1450 m and 2450 m below the surface at the geographic South Pole to detect neutrinos via Cherenkov radiation of relativistic charged particles produced in their interactions. This detector is responsible for a number of key observations in neutrino astrophysics, which include the discovery of a high-energy astrophysical neutrino flux and, more recently, the galactic plane. During the austral summer of 2025/26, five new strings equipped with new photosensor designs were deployed as a dense infill in the middle of the existing detector. The science goals of this detector are twofold: Firstly, given the higher photocathode density, an improved atmospheric neutrino event selection and reconstruction at a few GeV can be achieved for enhanced capabilities to study neutrino oscillations. Secondly, novel calibration devices will improve the knowledge of the optical properties of the glacial ice and the detector response. These new calibration results will be applied to archival IceCube data, improving angular and spatial resolution of all detected astrophysical neutrino events. The IceCube Upgrade also serves as a first step towards the next-generation neutrino telescope at the South Pole, called IceCube-Gen2.

astro-ph.IM↗