scholarly journals Azimuth Ambiguity Suppression in SAR Images Based on VS-KSVD Dictionary Learning and Compressive Sensing

2021 ◽  
Vol 2083 (3) ◽  
pp. 032049
Author(s):  
Xinchang Hu ◽  
Pengbo Wang ◽  
Yanan Guo ◽  
Qian Han ◽  
Xinkai Zhou
Keyword(s):  
Dictionary Learning ◽  
Image Interpretation ◽  
Statistical Characteristics ◽  
Sar Images ◽  
Edge Information ◽  
Frequency Domains ◽  
Under Sampling ◽  
High Resolution Images ◽  
Novel Method

Abstract The azimuth ambiguities appear widely in Synthetic Aperture Radar (SAR) images, which causes a large number of false targets and seriously affect the quality of image interpretation. Due to under-sampling in Doppler domain, ambiguous energy is mixed with energy from the main zone in the time and frequency domains. In order to effectively suppress the ambiguous energy in SAR images without loss of resolution, this paper presents a novel method of KSVD dictionary learning based on variance statistics (VS-KSVD) and compressed sensing (CS) reconstruction. According to the statistical characteristics of distributed targets, the dictionary that represents the ambiguities is selected and suppressed by coefficient weighting, in which local window filtering is carried out to remove the block effect and optimize the edge information. Finally, the high resolution images with low-ambiguity can be reconstructed by CS. With the proposed approach, the feasibility and effectiveness of the proposed approach is validated by using satellite data and simulation in suppressing azimuth ambiguity.

scholarly journals HOLBP: Remote Sensing Image Registration Based on Histogram of Oriented Local Binary Pattern Descriptor

2021 ◽  
Vol 13 (12) ◽  
pp. 2328
Author(s):  
Yameng Hong ◽  
Chengcai Leng ◽  
Xinyue Zhang ◽  
Zhao Pei ◽  
Irene Cheng ◽  
...  
Keyword(s):  
Image Registration ◽  
Local Binary Pattern ◽  
Computational Time ◽  
Rotation Invariant ◽  
Edge Information ◽  
Important Research Topic ◽  
New Construction ◽  
Novel Method ◽  
Direction Information ◽  
Angle Calculation

Image registration has always been an important research topic. This paper proposes a novel method of constructing descriptors called the histogram of oriented local binary pattern descriptor (HOLBP) for fast and robust matching. There are three new components in our algorithm. First, we redefined the gradient and angle calculation template to make it more sensitive to edge information. Second, we proposed a new construction method of the HOLBP descriptor and improved the traditional local binary pattern (LBP) computation template. Third, the principle of uniform rotation-invariant LBP was applied to add 10-dimensional gradient direction information to form a 138-dimension HOLBP descriptor vector. The experimental results showed that our method is very stable in terms of accuracy and computational time for different test images.

scholarly journals AI-based localization and classification of skin disease with erythema

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ha Min Son ◽  
Wooho Jeon ◽  
Jinhyun Kim ◽  
Chan Yeong Heo ◽  
Hye Jin Yoon ◽  
...  
Keyword(s):  
Neural Network ◽  
Skin Diseases ◽  
Classification Model ◽  
Screening Tests ◽  
Sensitivity Score ◽  
Common Skin ◽  
Novel Method ◽  
Improved Performance ◽  
High Level

AbstractAlthough computer-aided diagnosis (CAD) is used to improve the quality of diagnosis in various medical fields such as mammography and colonography, it is not used in dermatology, where noninvasive screening tests are performed only with the naked eye, and avoidable inaccuracies may exist. This study shows that CAD may also be a viable option in dermatology by presenting a novel method to sequentially combine accurate segmentation and classification models. Given an image of the skin, we decompose the image to normalize and extract high-level features. Using a neural network-based segmentation model to create a segmented map of the image, we then cluster sections of abnormal skin and pass this information to a classification model. We classify each cluster into different common skin diseases using another neural network model. Our segmentation model achieves better performance compared to previous studies, and also achieves a near-perfect sensitivity score in unfavorable conditions. Our classification model is more accurate than a baseline model trained without segmentation, while also being able to classify multiple diseases within a single image. This improved performance may be sufficient to use CAD in the field of dermatology.

scholarly journals A novel p-harmonic descent approach applied to fluid dynamic shape optimization

2021 ◽  
Author(s):  
Peter Marvin Müller ◽  
Niklas Kühl ◽  
Martin Siebenborn ◽  
Klaus Deckelnick ◽  
Michael Hinze ◽  
...  
Keyword(s):  
Shape Optimization ◽  
Large Deformations ◽  
Fluid Dynamic ◽  
Shape Optimisation ◽  
Shape Features ◽  
Floating Bodies ◽  
Novel Method ◽  
Sharp Corners ◽  
Dynamic Shape

AbstractWe introduce a novel method for the implementation of shape optimization for non-parameterized shapes in fluid dynamics applications, where we propose to use the shape derivative to determine deformation fields with the help of the $$p-$$ p - Laplacian for $$p > 2$$ p > 2 . This approach is closely related to the computation of steepest descent directions of the shape functional in the $$W^{1,\infty }-$$ W 1 , ∞ - topology and refers to the recent publication Deckelnick et al. (A novel $$W^{1,\infty}$$ W 1 , ∞ approach to shape optimisation with Lipschitz domains, 2021), where this idea is proposed. Our approach is demonstrated for shape optimization related to drag-minimal free floating bodies. The method is validated against existing approaches with respect to convergence of the optimization algorithm, the obtained shape, and regarding the quality of the computational grid after large deformations. Our numerical results strongly indicate that shape optimization related to the $$W^{1,\infty }$$ W 1 , ∞ -topology—though numerically more demanding—seems to be superior over the classical approaches invoking Hilbert space methods, concerning the convergence, the obtained shapes and the mesh quality after large deformations, in particular when the optimal shape features sharp corners.

scholarly journals ART-UP: A Novel Method for Generating Scanning-Robust Aesthetic QR Codes

2021 ◽  
Vol 17 (1) ◽  
pp. 1-23
Author(s):  
Mingliang Xu ◽  
Qingfeng Li ◽  
Jianwei Niu ◽  
Hao Su ◽  
Xiting Liu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Qr Code ◽  
Quick Response ◽  
Estimation Model ◽  
Qr Codes ◽  
Excellent Performance ◽  
Novel Method ◽  
Coarse To Fine

Quick response (QR) codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this article, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.

scholarly journals AB0050 A NOVEL METHOD FOR ISOLATION OF EXOSOMES FROM SYNOVIAL FLUID

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1057.2-1057
Author(s):  
Y. Liu ◽  
Y. Huang ◽  
Q. Huang ◽  
S. Sun ◽  
Z. Ji ◽  
...  
Keyword(s):  
Synovial Fluid ◽  
Western Blot ◽  
Biological Fluid ◽  
High Sensitivity ◽  
Protein Distribution ◽  
Sds Page ◽  
Close Relationship ◽  
Novel Method ◽  
Low Levels

Background:Exosomes in synovial fluid (SF) has a close relationship with the pathogenesis of rheumatiod arthritis. As a complex biological fluid, SF presents challenges for exosomes isolation using standard methods, such as ExoquickTM kit and ultracentrifugation.Objectives:The study aims to compared the quality of exosomes separated by ExoquickTM kit (TM), ExoquickTM kit+ExoquickTC kit (TM-TC), ultracentrifugation (UC) and TM-TC+UC(TM-TC-UC) from SF.Methods:Exosomes was separated by TM, TM-TC, UC and TM-TC-UC respectively. The size and concentrations of exosomes were detected by high sensitivity flow cytometry for nanoparticle analysis. Total protein and RNA were extracted from exosomes. SDS-PAGE was used to detect the protein distribution of exosomes. Western blot was used to examine the level of albumin and exosomes marker (TSG101 and CD81).Results:There was no statistic difference in the diameters of exosomes separated by the four methods. The concentrations of exosomes in TM, TM-TC, TM-TC-UC and UC were (5.65±0.93), (3.02±1.19), (1.67±0.25) and (4.61±0.73) *109Particles/mL. The protein concentrations of exosomes separated by the four methods were consistent with the concentrations of exosomes. SDS-PAGE showed that the protein distribution of exosomes separated by the four methods were different. Low levels of albumin were detected in TM-TC and TM-TC-UC, while high levels of albumin in TM and UC. Total RNA concentrations from exosomes in TM-TC was higher than other groups.Conclusion:TM-TC can be used to obtain higher quality exosomes from SF for the study of exosome-enriched components.References:[1]Helwa I, et al, A Comparative Study of Serum Exosome Isolation Using Differential Ultracentrifugation and Three Commercial Reagents. PloS one, 2017. 12(1): p. e0170628-e0170628.Figure 1.A: SDS-PAGE showed the protein distribution of exosomes; B: the detection of albumin, TSG101 and CD81 by western blot.Disclosure of Interests:None declared

scholarly journals Using Sentinel-2 Images to Estimate Topography, Tidal-Stage Lags and Exposure Periods over Large Intertidal Areas

2021 ◽  
Vol 13 (2) ◽  
pp. 320
Author(s):  
José P. Granadeiro ◽  
João Belo ◽  
Mohamed Henriques ◽  
João Catalão ◽  
Teresa Catry
Keyword(s):  
Large Scale ◽  
Exposure Period ◽  
Intertidal Area ◽  
Digital Elevation ◽  
Geographical Bias ◽  
Novel Method ◽  
Tidal Stage ◽  
Sentinel 2

Intertidal areas provide key ecosystem services but are declining worldwide. Digital elevation models (DEMs) are important tools to monitor the evolution of such areas. In this study, we aim at (i) estimating the intertidal topography based on an established pixel-wise algorithm, from Sentinel-2 MultiSpectral Instrument scenes, (ii) implementing a set of procedures to improve the quality of such estimation, and (iii) estimating the exposure period of the intertidal area of the Bijagós Archipelago, Guinea-Bissau. We first propose a four-parameter logistic regression to estimate intertidal topography. Afterwards, we develop a novel method to estimate tide-stage lags in the area covered by a Sentinel-2 scene to correct for geographical bias in topographic estimation resulting from differences in water height within each image. Our method searches for the minimum differences in height estimates obtained from rising and ebbing tides separately, enabling the estimation of cotidal lines. Tidal-stage differences estimated closely matched those published by official authorities. We re-estimated pixel heights from which we produced a model of intertidal exposure period. We obtained a high correlation between predicted and in-situ measurements of exposure period. We highlight the importance of remote sensing to deliver large-scale intertidal DEM and tide-stage data, with relevance for coastal safety, ecology and biodiversity conservation.

Soft Reduction of a Cast Ingot on the Incomplete Crystallization Stage

2013 ◽  
Vol 762 ◽  
pp. 261-265 ◽  
Author(s):  
Tanya I. Cherkashina ◽  
Igor Mazur ◽  
Sergey A. Aksenov
Keyword(s):  
Metal Forming ◽  
Physical Simulation ◽  
Fluid Layer ◽  
Liquid Core ◽  
Soft Reduction ◽  
Deformation Processes ◽  
Novel Method ◽  
Full Scale Tests ◽  
Crystallization Stage

Numerical and physical simulation on model samples can provide data for various aspects of metal forming, without resorting to time-consuming and costly full-scale tests. This paper presents examples of modeling of the deformation of a slab with a liquid core. The use of soft reduction can enhance the homogeneity of the structure, which improves the quality of cast billets. Mathematical modeling is described here where the fluid layer is taken into account by the influence of boundary conditions in the crust in the form of ferrostatic pressure, which allows calculation of the intensity of deformation, total deformation and strain. It also provides a novel method for studying the process of soft reduction. It is based on a physical model of the slab consisting of a closed solid shell made of a calibrated lead shot and the Wood's alloy. To simulate the liquid molten metal, the interior of the shell is filled with gelatin. This approach can be applied to further studies on deformation processes and the penetration of deformation into complex metallic systems.

scholarly journals Cloud Computation Using High-Resolution Images for Improving the SDG Indicator on Open Spaces

2020 ◽  
Vol 12 (7) ◽  
pp. 1144
Author(s):  
Rosa Aguilar ◽  
Monika Kuffer
Keyword(s):  
High Resolution ◽  
Open Space ◽  
Local Planning ◽  
Open Spaces ◽  
High Resolution Imagery ◽  
Coarse Spatial Resolution ◽  
Multi Temporal ◽  
High Resolution Images ◽  
Cloud Computation

Open spaces are essential for promoting quality of life in cities. However, accelerated urban growth, in particular in cities of the global South, is reducing the often already limited amount of open spaces with access to citizens. The importance of open spaces is promoted by SDG indicator 11.7.1; however, data on this indicator are not readily available, neither globally nor at the metropolitan scale in support of local planning, health and environmental policies. Existing global datasets on built-up areas omit many open spaces due to the coarse spatial resolution of input imagery. Our study presents a novel cloud computation-based method to map open spaces by accessing the multi-temporal high-resolution imagery repository of Planet. We illustrate the benefits of our proposed method for mapping the dynamics and spatial patterns of open spaces for the city of Kampala, Uganda, achieving a classification accuracy of up to 88% for classes used by the Global Human Settlement Layer (GHSL). Results show that open spaces in the Kampala metropolitan area are continuously decreasing, resulting in a loss of open space per capita of approximately 125 m2 within eight years.

A Novel Method of Detecting Measurement Uncertainty of Voltage Deviation

2013 ◽  
Vol 805-806 ◽  
pp. 688-692
Author(s):  
Xin Fang ◽  
Xue Liang Huang ◽  
Yan Zhu
Keyword(s):  
Measurement Uncertainty ◽  
Power Quality ◽  
National Standards ◽  
Measurement Time ◽  
Time Interval ◽  
Basic Measurement ◽  
Voltage Deviation ◽  
Novel Method ◽  
Simulation Results

Nowadays, there are various devices to detect the power quality of AC grid, where uncertainty of voltage deviation is an important parameter to investigate the power quality. National standards specify several sinusoidal waveforms to detect it, usually implemented into the detecting devices. But these waveforms are not enough and a novel method of detecting measurement uncertainty of voltage deviation is proposed in this paper. A series of detection waveforms are designed using this method. The simulation results verify that the method is available to measure uncertainty of voltage deviation more accurately. Moreover, it can be used to justify whether the basic measurement time interval of voltage deviation meets IEC standard requirements.

scholarly journals Observing merger trees in a new light

2018 ◽  
Vol 35 ◽  
Author(s):  
Rhys J. J. Poulton ◽  
Aaron S. G. Robotham ◽  
Chris Power ◽  
Pascal J. Elahi
Keyword(s):  
Dark Matter ◽  
Galaxy Formation ◽  
Diagnostic Tool ◽  
Cosmic Time ◽  
Analytical Models ◽  
Dark Matter Halos ◽  
Assembly Simulation ◽  
Novel Method ◽  
Tree Building

AbstractMerger trees harvested from cosmologicalN-body simulations encode the assembly histories of dark matter halos over cosmic time and are a fundamental component of semi-analytical models of galaxy formation. The ability to compare the tools used to construct merger trees, namely halo finders and tree building algorithms, in an unbiased and systematic manner is critical to assess the quality of merger trees. In this paper, we present the dendrogram, a novel method to visualise merger trees, which provides a comprehensive characterisation of a halo’s assembly history—tracking subhalo orbits, halo merger events, and the general evolution of halo properties. We show the usefulness of thedendrogramas a diagnostic tool of merger trees by comparing halo assembly simulation analysed with three different halo finders—VELOCIraptor, AHF, and Rockstar—and their associated tree builders. Based on our analysis of the resulting dendrograms, we highlight how they have been used to motivate improvements to VELOCIraptor. Thedendrogramsoftware is publicly available online, at:https://github.com/rhyspoulton/MergerTree-Dendrograms.

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