Related papers: Resolution limits in astronomical images
Supernova (SN) rates serve as an important probe of star-formation models and initial mass functions. Near-infrared seeing-limited ground-based surveys typically discover a factor of 3-10 fewer SNe than predicted from far-infrared (FIR)…
Super-resolution imaging has revolutionized the study of systems ranging from molecular structures to distant galaxies. However, existing super-resolution methods require extensive calibration and retraining for each imaging setup, limiting…
We present imaging data and photometry for the COSMOS survey in 15 photometric bands between 0.3um and 2.4um. These include data taken on the Subaru 8.3m telescope, the KPNO and CTIO 4m telescopes, and the CFHT 3.6m telescope. Special…
We present a catalog of J-band (1.08 um to 1.35 um) stellar spectra at low resolution (R ~ 400). The targets consist of 105 stars ranging in spectral type from O9.5 to M7 and luminosity classes I through V. The relatively featureless…
High-resolution radar range profile (RRP) is crucial for accurate target recognition and scene perception. To get a high-resolution RRP, many methods have been developed, such as multiple signal classification (MUSIC), orthogonal matching…
We present the first three-dimensional theoretical model of microparticle-assisted super-resolution imaging, enabling accurate simulation of virtual image formation. The model reveals that accounting for partial spatial coherence of…
We review the systematic uncertainties that have plagued attempts to obtain high precision and high accuracy from ground-based photometric measurements using CCDs. We identify two main challenges in breaking through the 1% precision…
Computer representations of real numbers are necessarily discrete, with some finite resolution, discreteness, quantization, or minimum representable difference. We perform astrometric and photometric measurements on stars and co-add…
Typical astronomical spectrographs have a resolution ranging between a few hundred to 200.000. Deconvolution and correlation techniques are being employed with a significance down to 1/1000 th of a pixel. HeAr and ThAr lamps are usually…
This paper discusses the broad science case for obtaining milliarcsecond to microarcsecond astronomical imaging resolution in the soft to medium-energy X-ray band (~0.5 to ~8 keV). Astronomy across much of the electromagnetic spectrum has…
The Swedish 1-m Solar Telescope (SST) offers excellent imaging quality, but it has a comparatively small field of view. This means that while observing the solar photosphere, there has been no convenient way of calibrating the image scale…
We consider passive imaging tasks involving discrimination between known candidate objects and investigate the best possible accuracy with which the correct object can be identified. We analytically compute quantum-limited error bounds for…
Spectra of the spreading layers on the neutron star surface are calculated on the basis of the Inogamov-Sunyaev model taking into account general relativity correction to the surface gravity and considering various chemical composition of…
Improving angular resolution is one of X-ray astronomy's big challenges. While X-ray interferometry should eventually vastly improve broad-band angular resolution, in the near-term, X-ray telescopes will sacrifice angular resolution for…
Two approaches (micro- and macro- investigations) are used to determine the dimension dependences of the optical parameters of the nanometer-scale layers of materials. It is shown that both an index of refraction and coefficient of…
A combined sample of 79 high and low redshift supernovae Ia (SNe) is used to set constraints on the degree of anisotropy in the Universe out to $z\simeq1$. First we derive the global most probable values of matter density $\Omega_M $, the…
In this paper a new method of image smoothing for satellite imagery and its applications in environmental remote sensing are presented. This method is based on the global gradient minimization over the whole image. With respect to the image…
We present a two-component Machine Learning (ML) based approach for classifying astronomical images by data-quality via an examination of sources detected in the images and image pixel values from representative sources within those images.…
We derive the fundamental limit to the resolution of far-field optical imaging, and demonstrate that, while a bound to the resolution of a fundamental nature does exit, contrary to the conventional wisdom it is neither exactly equal to nor…
We develop an imaging algorithm that exploits strong scattering to achieve super-resolution in changing random media. The method processes large and diverse array datasets using sparse dictionary learning, clustering, and multidimensional…