90 research outputs found
No-Reference Light Field Image Quality Assessment Based on Micro-Lens Image
Light field image quality assessment (LF-IQA) plays a significant role due to
its guidance to Light Field (LF) contents acquisition, processing and
application. The LF can be represented as 4-D signal, and its quality depends
on both angular consistency and spatial quality. However, few existing LF-IQA
methods concentrate on effects caused by angular inconsistency. Especially,
no-reference methods lack effective utilization of 2-D angular information. In
this paper, we focus on measuring the 2-D angular consistency for LF-IQA. The
Micro-Lens Image (MLI) refers to the angular domain of the LF image, which can
simultaneously record the angular information in both horizontal and vertical
directions. Since the MLI contains 2-D angular information, we propose a
No-Reference Light Field image Quality assessment model based on MLI (LF-QMLI).
Specifically, we first utilize Global Entropy Distribution (GED) and Uniform
Local Binary Pattern descriptor (ULBP) to extract features from the MLI, and
then pool them together to measure angular consistency. In addition, the
information entropy of Sub-Aperture Image (SAI) is adopted to measure spatial
quality. Extensive experimental results show that LF-QMLI achieves the
state-of-the-art performance
Quality Assessment of Stereoscopic 360-degree Images from Multi-viewports
Objective quality assessment of stereoscopic panoramic images becomes a
challenging problem owing to the rapid growth of 360-degree contents. Different
from traditional 2D image quality assessment (IQA), more complex aspects are
involved in 3D omnidirectional IQA, especially unlimited field of view (FoV)
and extra depth perception, which brings difficulty to evaluate the quality of
experience (QoE) of 3D omnidirectional images. In this paper, we propose a
multi-viewport based fullreference stereo 360 IQA model. Due to the freely
changeable viewports when browsing in the head-mounted display (HMD), our
proposed approach processes the image inside FoV rather than the projected one
such as equirectangular projection (ERP). In addition, since overall QoE
depends on both image quality and depth perception, we utilize the features
estimated by the difference map between left and right views which can reflect
disparity. The depth perception features along with binocular image qualities
are employed to further predict the overall QoE of 3D 360 images. The
experimental results on our public Stereoscopic OmnidirectionaL Image quality
assessment Database (SOLID) show that the proposed method achieves a
significant improvement over some well-known IQA metrics and can accurately
reflect the overall QoE of perceived images
Ionic Liquids as Bifunctional Cosolvents Enhanced CO<sub>2</sub> Conversion Catalysed by NADH-Dependent Formate Dehydrogenase
Efficient CO2 conversion by formate dehydrogenase is limited by the low CO2 concentrations that can be reached in traditional buffers. The use of ionic liquids was proposed as a manner to increase CO2 concentration in the reaction system. It has been found, however, that the required cofactor (NADH) heavily degraded during the enzymatic reaction and that acidity was the main reason. Acidity, indeed, resulted in reduction of the conversion of CO2 into formic acid and contributed to overestimate the amount of formic acid produced when the progression of the reaction was followed by a decrease in NADH absorbance (method N). Stability of NADH and the mechanism of NADH degradation was investigated by UV, NMR and by DFT calculations. It was found that by selecting neutral-basic ionic liquids and by adjusting the concentration of the ionic liquid in the buffer, the concentration of NADH can be maintained in the reaction system with little loss. Conversion of CO2 to methanol in BmimBF(4) (67.1%) was more than twice as compared with the conversion attained by the enzymatic reaction in phosphate buffer (24.3%)
FacetClumps: A Facet-based Molecular Clump Detection Algorithm
A comprehensive understanding of molecular clumps is essential for
investigating star formation. We present an algorithm for molecular clump
detection, called FacetClumps. This algorithm uses a morphological approach to
extract signal regions from the original data. The Gaussian Facet model is
employed to fit the signal regions, which enhances the resistance to noise and
the stability of the algorithm in diverse overlapping areas. The introduction
of the extremum determination theorem of multivariate functions offers
theoretical guidance for automatically locating clump centers. To guarantee
that each clump is continuous, the signal regions are segmented into local
regions based on gradient, and then the local regions are clustered into the
clump centers based on connectivity and minimum distance to identify the
regional information of each clump. Experiments conducted with both simulated
and synthetic data demonstrate that FacetClumps exhibits great recall and
precision rates, small location error and flux loss, a high consistency between
the region of detected clump and that of simulated clump, and is generally
stable in various environments. Notably, the recall rate of FacetClumps in the
synthetic data, which comprises () emission line of the
MWISP within , and 5 km s 35 km s and simulated
clumps, reaches 90.2\%. Additionally, FacetClumps demonstrates satisfactory
performance when applied to observational data.Comment: 27pages,28figure
Monolithic growth of InAs quantum dots lasers on (001) silicon emitting at 1.55 μm
Broad-area 1.55 μm InAs quantum dots (QDs) lasers were fabricated based on monolithic growth of InAs/InAlGaAs/InP active structures on nano-patterned (001) silicon substrates. Device optoelectronic properties and materials' optical gain and absorption features were studied to provide experimental support for further optimizations in laser design
- …