Perceptual Quality Assessment Based on Visual Attention Analysis

Most existing quality metrics do not take the human attention analysis into account. Attention to particular objects or regions is an important attribute of human vision and perception system in measuring perceived image and video qualities. This paper presents an approach for extracting visual attention regions based on a combination of a bottom-up saliency model and semantic image analysis. The use of PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural SIMilarity) in extracted attention regions is analyzed for image/video quality assessment, and a novel quality metric is proposed which can exploit the attributes of visual attention information adequately. The experimental results with respect to the subjective measurement demonstrate that the proposed metric outperforms the current methods

Leveraging progressive model and overfitting for efficient learned image compression

Deep learning is overwhelmingly dominant in the field of computer vision and image/video processing for the last decade. However, for image and video compression, it lags behind the traditional techniques based on discrete cosine transform (DCT) and linear filters. Built on top of an autoencoder architecture, learned image compression (LIC) systems have drawn enormous attention in recent years. Nevertheless, the proposed LIC systems are still inferior to the state-of-the-art traditional techniques, for example, the Versatile Video Coding (VVC/H.266) standard, due to either their compression performance or decoding complexity. Although claimed to outperform the VVC/H.266 on a limited bit rate range, some proposed LIC systems take over 40 seconds to decode a 2K image on a GPU system. In this paper, we introduce a powerful and flexible LIC framework with multi-scale progressive (MSP) probability model and latent representation overfitting (LOF) technique. With different predefined profiles, the proposed framework can achieve various balance points between compression efficiency and computational complexity. Experiments show that the proposed framework achieves 2.5%, 1.0%, and 1.3% Bjontegaard delta bit rate (BD-rate) reduction over the VVC/H.266 standard on three benchmark datasets on a wide bit rate range. More importantly, the decoding complexity is reduced from O(n) to O(1) compared to many other LIC systems, resulting in over 20 times speedup when decoding 2K images

Observational signatures of microlensing in gravitational waves at LIGO/Virgo frequencies

Microlenses with typical stellar masses (a few ${\rm M}_{\odot}$) have traditionally been disregarded as potential sources of gravitational lensing effects at LIGO/Virgo frequencies, since the time delays are often much smaller than the inverse of the frequencies probed by LIGO/Virgo, resulting in negligible interference effects at LIGO/Virgo frequencies. While this is true for isolated microlenses in this mass regime, we show how, under certain circumstances and for realistic scenarios, a population of microlenses (for instance stars and remnants from a galaxy halo or from the intracluster medium) embedded in a macromodel potential (galaxy or cluster) can conspire together to produce time delays of order one millisecond which would produce significant interference distortions in the observed strains. At sufficiently large magnification factors (of several hundred), microlensing effects should be common in gravitationally lensed gravitational waves. We explore the regime where the predicted signal falls in the frequency range probed by LIGO/Virgo. We find that stellar mass microlenses, permeating the lens plane, and near critical curves, can introduce interference distortions in strongly lensed gravitational waves. For those lensed events with negative parity, (or saddle points, never studied before in the context of gravitational waves), and that take place near caustics of macromodels, they are more likely to produce measurable interference effects at LIGO/Virgo frequencies. This is the first study that explores the effect of a realistic population of microlenses, plus a macromodel, on strongly lensed gravitational waves.Comment: 16 page

A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data

<p>Abstract</p> <p>Background</p> <p>A key challenge in metabonomics is to uncover quantitative associations between multidimensional spectroscopic data and biochemical measures used for disease risk assessment and diagnostics. Here we focus on clinically relevant estimation of lipoprotein lipids by ¹H NMR spectroscopy of serum.</p> <p>Results</p> <p>A Bayesian methodology, with a biochemical motivation, is presented for a real ¹H NMR metabonomics data set of 75 serum samples. Lipoprotein lipid concentrations were independently obtained for these samples via ultracentrifugation and specific biochemical assays. The Bayesian models were constructed by Markov chain Monte Carlo (MCMC) and they showed remarkably good quantitative performance, the predictive R-values being 0.985 for the very low density lipoprotein triglycerides (VLDL-TG), 0.787 for the intermediate, 0.943 for the low, and 0.933 for the high density lipoprotein cholesterol (IDL-C, LDL-C and HDL-C, respectively). The modelling produced a kernel-based reformulation of the data, the parameters of which coincided with the well-known biochemical characteristics of the ¹H NMR spectra; particularly for VLDL-TG and HDL-C the Bayesian methodology was able to clearly identify the most characteristic resonances within the heavily overlapping information in the spectra. For IDL-C and LDL-C the resulting model kernels were more complex than those for VLDL-TG and HDL-C, probably reflecting the severe overlap of the IDL and LDL resonances in the ¹H NMR spectra.</p> <p>Conclusion</p> <p>The systematic use of Bayesian MCMC analysis is computationally demanding. Nevertheless, the combination of high-quality quantification and the biochemical rationale of the resulting models is expected to be useful in the field of metabonomics.</p

Cancer risk in hospitalised psoriasis patients: a follow-up study in Sweden

We examined overall and specific cancer risks among Swedish subjects who had been hospitalised one or more times for psoriasis. A database was created by identifying such patients from the Swedish Hospital Discharge Register and linking them with the Cancer Registry. Follow-up of patients was carried out from the last hospitalisation through 2004. A total of 15 858 patients were hospitalised for psoriasis during 1965–2004, of whom 1408 developed cancer, giving an overall standardised incidence ratios (SIRs) of 1.33. A significant excess was noted for squamous cell skin cancer, and for cancers of the upper aerodigestive tract, oesophagus, stomach, liver, pancreas, lung, kidney and bladder as well as non-Hodgkin lymphoma. Many of these may reflect the effects of alcohol drinking and tobacco smoking. Patients with multiple hospitalisations showed high risk, particularly for oesophageal (SIR 6.97) and skin (SIR 4.76) cancers

Genetic evolution of invasive emm28 Streptococcus pyogenes strains and significant association with puerperal infections in young women in Finland

Objectives: Streptococcus pyogenes or group A streptococcus (GAS) is a human specific pathogen that annually infects over 700 million individuals. GAS strains of type emm28 are an abundant cause of invasive infections in Europe and North America.Methods: We conducted a population-based study on bacteraemic emm28 GAS cases in Finland, from 1995 to 2015. Whole-genome sequencing (WGS) was used to genetically characterize the bacterial isolates. Bayesian analysis of the population structure was used to define genetic clades. Register-linkage analysis was performed to test for association of emm28 GAS with delivery- or postpartum-related infections. A genome-wide association study was used to search for DNA sequences associated with delivery or puerperal infections.Results: Among 3060 bacteraemic cases reported during the study period, 714 were caused by emm28. Women comprised a majority of cases (59 %, 422/714), and were significantly over-represented (84.4 %, 162/192, p Conclusions: Women of childbearing age were significantly overrepresented among bacteraemic emm28 GAS cases, and in particular were strongly associated with delivery and puerperium cases over the 21 years studied. The molecular mechanisms behind these associations are unclear and warrant further investigation.</p