12,339 research outputs found
Burst Denoising with Kernel Prediction Networks
We present a technique for jointly denoising bursts of images taken from a
handheld camera. In particular, we propose a convolutional neural network
architecture for predicting spatially varying kernels that can both align and
denoise frames, a synthetic data generation approach based on a realistic noise
formation model, and an optimization guided by an annealed loss function to
avoid undesirable local minima. Our model matches or outperforms the
state-of-the-art across a wide range of noise levels on both real and synthetic
data.Comment: To appear in CVPR 2018 (spotlight). Project page:
http://people.eecs.berkeley.edu/~bmild/kpn
Mitigation of Side-Effect Modulation in Optical OFDM VLC Systems
Side-effect modulation (SEM) has the potential to be a significant source of
interference in future visible light communication (VLC) systems. SEM is a
variation in the intensity of the light emitted by a luminaire and is usually a
side-effect caused by the power supply used to drive the luminaires. For LED
luminaires powered by a switched mode power supply, the SEM can be at much
higher frequencies than that emitted by conventional incandescent or
fluorescent lighting. It has been shown that the SEM caused by commercially
available LED luminaires is often periodic and of low power. In this paper, we
investigate the impact of typical forms of SEM on the performance of optical
OFDM VLC systems; both ACO-OFDM and DCO-OFDM are considered. Our results show
that even low levels of SEM power can significantly degrade the bit-error-rate
performance. To solve this problem, an SEM mitigation scheme is described. The
mitigation scheme is decision-directed and is based on estimating and
subtracting the fundamental component of the SEM from the received signal. We
describe two forms of the algorithm; one uses blind estimation while the other
uses pilot-assisted estimation based on a training sequence. Decision errors,
resulting in decision noise, limit the performance of the blind estimator even
when estimation is based on very long signals. However, the pilot system can
achieve more accurate estimations, thus better performance. Results are first
presented for typical SEM waveforms for the case where the fundamental
frequency of the SEM is known. The algorithms are then extended to include a
frequency estimation step and the mitigation algorithm is shown also to be
effective in this case
Lack of clustering in low-redshift 21-cm intensity maps cross-correlated with 2dF galaxy densities
We report results from 21-cm intensity maps acquired from the Parkes radio
telescope and cross-correlated with galaxy maps from the 2dF galaxy survey. The
data span the redshift range and cover approximately 1,300
square degrees over two long fields. Cross correlation is detected at a
significance of . The amplitude of the cross-power spectrum is low
relative to the expected dark matter power spectrum, assuming a neutral
hydrogen (HI) bias and mass density equal to measurements from the ALFALFA
survey. The decrement is pronounced and statistically significant at small
scales. At , the cross power spectrum is more
than a factor of 6 lower than expected, with a significance of .
This decrement indicates either a lack of clustering of neutral hydrogen (HI),
a small correlation coefficient between optical galaxies and HI, or some
combination of the two. Separating 2dF into red and blue galaxies, we find that
red galaxies are much more weakly correlated with HI on scales, suggesting that HI is more associated with blue
star-forming galaxies and tends to avoid red galaxies.Comment: 12 pages, 3 figures; fixed typo in meta-data title and paper author
- …