scholarly journals Advanced Visualization Polarimetric Imaging: Removal of Water Spray Effect Utilizing Circular Polarization

2021 ◽  
Vol 11 (7) ◽  
pp. 2996
Author(s):  
Fei Liu ◽  
Xuan Li ◽  
Pingli Han ◽  
Xiaopeng Shao
Keyword(s):  
Circular Polarization ◽  
Low Frequency ◽  
Propagation Distance ◽  
Imaging Method ◽  
Water Spray ◽  
Circularly Polarized ◽  
Structure Information ◽  
Multi Scale ◽  
Multi Scales

Circular polarization (CP) memory is a well-known phenomenon whereby natural light becomes partially circularly polarized after scattering by water spray several times, and the circularly polarized state can be well preserved within a certain propagation distance. In this study, a CP imaging method combined with the multi-scale analysis in the frequency domain is proposed to enhance the vision in rainy conditions. The images were first decomposed into multi-scales. CP characteristics of light were employed in the low-frequency parts to improve the quality of images in rainy conditions, and the high-frequency parts compensated specific structure information. Experimental results demonstrate that the proposed method can remove the water spray effect thereby improving the vision of degraded rainy-day images.

scholarly journals Pansharpening with a Gradient Domain GIF Based on NSST

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 229
Author(s):  
Jiao Jiao ◽  
Lingda Wu
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Objective Evaluation ◽  
Data Sets ◽  
Multi Scale ◽  
Guided Image Filter ◽  
Gradient Domain ◽  
Spatial Quality

In order to improve the fusion quality of multispectral (MS) and panchromatic (PAN) images, a pansharpening method with a gradient domain guided image filter (GIF) that is based on non-subsampled shearlet transform (NSST) is proposed. First, multi-scale decomposition of MS and PAN images is performed by NSST. Second, different fusion rules are designed for high- and low-frequency coefficients. A fusion rule that is based on morphological filter-based intensity modulation (MFIM) technology is proposed for the low-frequency coefficients, and the edge refinement is carried out based on a gradient domain GIF to obtain the fused low-frequency coefficients. For the high-frequency coefficients, a fusion rule based on an improved pulse coupled neural network (PCNN) is adopted. The gradient domain GIF optimizes the firing map of the PCNN model, and then the fusion decision map is calculated to guide the fusion of the high-frequency coefficients. Finally, the fused high- and low-frequency coefficients are reconstructed with inverse NSST to obtain the fusion image. The proposed method was tested using the WorldView-2 and QuickBird data sets; the subjective visual effects and objective evaluation demonstrate that the proposed method is superior to the state-of-the-art pansharpening methods, and it can efficiently improve the spatial quality and spectral maintenance.

Fusion of Polarization Image Based on Curvelet Transform

2014 ◽  
Vol 536-537 ◽  
pp. 111-114 ◽  
Author(s):  
De Xiang Zhang ◽  
Hong Hai Wang ◽  
Feng Xue
Keyword(s):  
Image Fusion ◽  
High Frequency ◽  
Low Frequency ◽  
Curvelet Transform ◽  
Fusion Algorithm ◽  
Information Measurement ◽  
Multi Scale ◽  
Fused Image ◽  
Polarization Image ◽  
Multi Scales

Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidly in the field of image fusion. Firstly, using the curvelet transform, several polarization images can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions. For the low-frequency coefficients, the average fusion method is used. For the each directional high frequency sub-band coefficients, the larger value of region variance information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused curvelet coefficients. In the present work an algorithm for image fusion based on the curvelet transform was implemented, analyzed, and compared with a wavelet-based fusion algorithm. Experimental results show that the proposed algorithm works better in preserving the edges and texture information compared with the wavelet-based image fusion algorithms.

scholarly journals Extended Subaperture Imaging Method for Airborne Low Frequency Ultrawideband SAR Data

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4516
Author(s):  
Daoxiang An ◽  
Wu Wang ◽  
Leping Chen
Keyword(s):  
Low Frequency ◽  
Synthetic Aperture ◽  
Imaging Method ◽  
Theory Analysis ◽  
Range Cell ◽  
Imaging Results ◽  
Sar Imaging ◽  
Sar Data ◽  
Range Cell Migration

The subaperture processing is one of the essential strategies for low frequency ultrawideband synthetic aperture radar (LF UWB SAR) imaging, especially for the real-time LF UWB SAR imaging because it can improve the parallelization of the imaging algorithm. However, due to the longer synthetic aperture of LF UWB SAR, the traditional subaperture imaging encounters an azimuth ambiguities problem, which severely degrades the focused quality of the imaging results. In this paper, the reason for the presence of azimuth ambiguities in the LF UWB SAR subaperture imaging and its influence on image quality is first analyzed in theory. Then, an extended subaperture imaging method based on the extension of subaperture length before Range Cell Migration Correction (RCMC) was proposed. By lengthening the subaperture length, the azimuth ambiguities are effectively eliminated. Finally, the extended part of subaperture is wiped off before the azimuth compression (AC), and the LF UWB SAR image of high focused quality is obtained. The correctness of the theory analysis and the effectiveness of the proposed method have been validated through simulated and real LF UWB SAR data.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

Dynamics of the processes in metal machining

1998 ◽  
Vol 2 ◽  
pp. 115-122
Author(s):  
Donatas Švitra ◽  
Jolanta Janutėnienė
Keyword(s):  
High Frequency ◽  
Machine Tools ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Low Frequency ◽  
Metal Cutting Machine ◽  
Cutting Machine ◽  
Metal Machining

In the practice of processing of metals by cutting it is necessary to overcome the vibration of the cutting tool, the processed detail and units of the machine tool. These vibrations in many cases are an obstacle to increase the productivity and quality of treatment of details on metal-cutting machine tools. Vibration at cutting of metals is a very diverse phenomenon due to both it’s nature and the form of oscillatory motion. The most general classification of vibrations at cutting is a division them into forced vibration and autovibrations. The most difficult to remove and poorly investigated are the autovibrations, i.e. vibrations arising at the absence of external periodic forces. The autovibrations, stipulated by the process of cutting on metalcutting machine are of two types: the low-frequency autovibrations and high-frequency autovibrations. When the low-frequency autovibration there appear, the cutting process ought to be terminated and the cause of the vibrations eliminated. Otherwise, there is a danger of a break of both machine and tool. In the case of high-frequency vibration the machine operates apparently quiently, but the processed surface feature small-sized roughness. The frequency of autovibrations can reach 5000 Hz and more.

Estimating the Quality of Thermionic Cathodes for Microwave Vacuum Tubes Using the Low-Frequency Noise Parameters

Vestnik MEI ◽  
2018 ◽  
Vol 5 (5) ◽  
pp. 120-127
Author(s):  
Mikhail D. Vorobyev ◽  
◽  
Dmitriy N. Yudaev ◽  
Andrey Yu. Zorin ◽  
◽  
...  
Keyword(s):  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Noise Parameters ◽  
Thermionic Cathodes ◽  
Vacuum Tubes

A Broadband Circularly Polarized Cross-slotted Patch Antenna with Horizontal Meandered Strip (HMS)

Frequenz ◽  
2020 ◽  
Vol 74 (5-6) ◽  
pp. 191-199
Author(s):  
M. K. Verma ◽  
Binod K. Kanaujia ◽  
J. P. Saini ◽  
Padam S. Saini
Keyword(s):  
Circular Polarization ◽  
Patch Antenna ◽  
Impedance Matching ◽  
Axial Ratio ◽  
Impedance Bandwidth ◽  
Radiation Patterns ◽  
Circularly Polarized ◽  
Feeding Technique

AbstractA broadband circularly polarized slotted square patch antenna with horizontal meandered strip (HMS) is presented and studied. The HMS feeding technique provides the good impedance matching and broadside symmetrical radiation patterns. A set of cross asymmetrical slots are etched on the radiating patch to realize the circular polarization. An electrically small stub is added on the edge of the antenna for further improvement in performance. Measured 10-dB impedance bandwidth (IBW) and 3-dB axial ratio bandwidth (ARBW) of the proposed antenna are 32.31 % (3.14–4.35 GHz) and 20.91 % (3.34–4.12 GHz), respectively. The gain of the antenna is varied from 3.5 to 4.86dBi within 3-dB ARBW. Measured results matched well with the simulated results.

scholarly journals Detection of Myocardial Infarction Using ECG and Multi-Scale Feature Concatenate

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1906
Author(s):  
Jia-Zheng Jian ◽  
Tzong-Rong Ger ◽  
Han-Hua Lai ◽  
Chi-Ming Ku ◽  
Chiung-An Chen ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Network Structure ◽  
Class Imbalance ◽  
Class Imbalance Problem ◽  
Multi Scale ◽  
Imbalance Problem ◽  
Average Accuracy ◽  
Significant Difference ◽  
Electrocardiogram Ecg

Diverse computer-aided diagnosis systems based on convolutional neural networks were applied to automate the detection of myocardial infarction (MI) found in electrocardiogram (ECG) for early diagnosis and prevention. However, issues, particularly overfitting and underfitting, were not being taken into account. In other words, it is unclear whether the network structure is too simple or complex. Toward this end, the proposed models were developed by starting with the simplest structure: a multi-lead features-concatenate narrow network (N-Net) in which only two convolutional layers were included in each lead branch. Additionally, multi-scale features-concatenate networks (MSN-Net) were also implemented where larger features were being extracted through pooling the signals. The best structure was obtained via tuning both the number of filters in the convolutional layers and the number of inputting signal scales. As a result, the N-Net reached a 95.76% accuracy in the MI detection task, whereas the MSN-Net reached an accuracy of 61.82% in the MI locating task. Both networks give a higher average accuracy and a significant difference of p < 0.001 evaluated by the U test compared with the state-of-the-art. The models are also smaller in size thus are suitable to fit in wearable devices for offline monitoring. In conclusion, testing throughout the simple and complex network structure is indispensable. However, the way of dealing with the class imbalance problem and the quality of the extracted features are yet to be discussed.

scholarly journals Non-Intrusive Load Disaggregation Based on a Multi-Scale Attention Residual Network

2020 ◽  
Vol 10 (24) ◽  
pp. 9132
Author(s):  
Liguo Weng ◽  
Xiaodong Zhang ◽  
Junhao Qian ◽  
Min Xia ◽  
Yiqing Xu ◽  
...  
Keyword(s):  
Smart Grids ◽  
Recognition Rate ◽  
Low Frequency ◽  
Attention Mechanism ◽  
Learning Ability ◽  
Residual Network ◽  
Multi Scale ◽  
Energy Disaggregation ◽  
Benchmark Datasets ◽  
Load Disaggregation

Non-intrusive load disaggregation (NILD) is of great significance to the development of smart grids. Current energy disaggregation methods extract features from sequences, and this process easily leads to a loss of load features and difficulties in detecting, resulting in a low recognition rate of low-use electrical appliances. To solve this problem, a non-intrusive sequential energy disaggregation method based on a multi-scale attention residual network is proposed. Multi-scale convolutions are used to learn features, and the attention mechanism is used to enhance the learning ability of load features. The residual learning further improves the performance of the algorithm, avoids network degradation, and improves the precision of load decomposition. The experimental results on two benchmark datasets show that the proposed algorithm has more advantages than the existing algorithms in terms of load disaggregation accuracy and judgments of the on/off state, and the attention mechanism can further improve the disaggregation accuracy of low-frequency electrical appliances.

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