302 research outputs found
Contrast Enhancement of Brightness-Distorted Images by Improved Adaptive Gamma Correction
As an efficient image contrast enhancement (CE) tool, adaptive gamma
correction (AGC) was previously proposed by relating gamma parameter with
cumulative distribution function (CDF) of the pixel gray levels within an
image. ACG deals well with most dimmed images, but fails for globally bright
images and the dimmed images with local bright regions. Such two categories of
brightness-distorted images are universal in real scenarios, such as improper
exposure and white object regions. In order to attenuate such deficiencies,
here we propose an improved AGC algorithm. The novel strategy of negative
images is used to realize CE of the bright images, and the gamma correction
modulated by truncated CDF is employed to enhance the dimmed ones. As such,
local over-enhancement and structure distortion can be alleviated. Both
qualitative and quantitative experimental results show that our proposed method
yields consistently good CE results
Acceleration of Histogram-Based Contrast Enhancement via Selective Downsampling
In this paper, we propose a general framework to accelerate the universal
histogram-based image contrast enhancement (CE) algorithms. Both spatial and
gray-level selective down- sampling of digital images are adopted to decrease
computational cost, while the visual quality of enhanced images is still
preserved and without apparent degradation. Mapping function calibration is
novelly proposed to reconstruct the pixel mapping on the gray levels missed by
downsampling. As two case studies, accelerations of histogram equalization (HE)
and the state-of-the-art global CE algorithm, i.e., spatial mutual information
and PageRank (SMIRANK), are presented detailedly. Both quantitative and
qualitative assessment results have verified the effectiveness of our proposed
CE acceleration framework. In typical tests, computational efficiencies of HE
and SMIRANK have been speeded up by about 3.9 and 13.5 times, respectively.Comment: accepted by IET Image Processin
A new characterization of fuzzy ideals of semigroups and its applications
In this paper, we develop a new technique for constructing fuzzy ideals of a semigroup. By using generalized Green\u27s relations, fuzzy star ideals are constructed. It is shown that the new fuzzy ideal of a semigroup can be used to investigate the relationship between fuzzy sets and abundance and regularity for an arbitrary semigroup. Appropriate examples of such fuzzy ideals are given in order to illustrate the technique. Finally, we explain when a semigroup satisfies conditions of regularity
On the Performances of Estimating Stellar Atmospheric Parameters from CSST Broad-band Photometry
Deriving atmospheric parameters of a large sample of stars is of vital
importance to understand the formation and evolution of the Milky Way.
Photometric surveys, especially those with near-ultraviolet filters, can offer
accurate measurements of stellar parameters, with the precision comparable to
that from low/medium resolution spectroscopy. In this study, we explore the
capability of measuring stellar atmospheric parameters from CSST broad-band
photometry (particularly the near-ultraviolet bands), based on synthetic colors
derived from model spectra. We find that colors from the optical and
near-ultraviolet filter systems adopted by CSST show significant sensitivities
to the stellar atmospheric parameters, especially the metallicity. According to
our mock data tests, the precision of the photometric metallicity is quite
high, with typical values of 0.17 dex and 0.20 dex for dwarf and giant stars,
respectively. The precision of the effective temperature estimated from
broad-band colors are within 50 K.Comment: 16 pages, 18 figures, accepted by Research in Astronomy and
Astrophysic
The Circular Velocity Curve of the Milky Way from 5 to 25 kpc using luminous red giant branch star
We present a sample of 254,882 luminous red giant branch (LRGB) stars
selected from the APOGEE and LAMOST surveys. By combining photometric and
astrometric information from the 2MASS and Gaia surveys, the precise distances
of the sample stars are determined by a supervised machine learning algorithm:
the gradient boosted decision trees. To test the accuracy of the derived
distances, member stars of globular clusters (GCs) and open clusters (OCs) are
used. The tests by cluster member stars show a precision of about 10 per cent
with negligible zero-point offsets, for the derived distances of our sample
stars. The final sample covers a large volume of the Galactic disk(s) and halo
of kpc and kpc. The rotation curve (RC) of the Milky
Way across radius of kpc have been accurately measured
with 54,000 stars of the thin disk population selected from the LRGB
sample. The derived RC shows a weak decline along with a gradient of
km s kpc,
in excellent agreement with the results measured by previous studies. The
circular velocity at the solar position, yielded by our RC, is
km s, again in great consistent
with other independent determinations. From the newly constructed RC, as well
as constraints from other data, we have constructed a mass model for our
Galaxy, yielding a mass of the dark matter halo of =
()10 with a corresponding radius of
= kpc and a local dark matter density of
GeV cm.Comment: 16 pages, 13 figures and 5 tables, accepted by Ap
2-Amino-5-methyl-6-methylsulfanyl-4-phenylbenzene-1,3-dicarbonitrile
The dihedral angle between the planes of the two aromatic rings of the title compound, C16H13N3S, is 56.7 (3)°. The crystal packing is stabilized by intermolecular N—H⋯N hydrogen bonds, which link the molecules into chains along [11]
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