Multispectral images based bridge detection method with RX detector

2014 ◽  
Author(s):  
Wei Wei ◽  
Yanning Zhang ◽  
Lei Zhang ◽  
Hangqi Yan ◽  
Bobo Wang
Keyword(s):  
Detection Method ◽  
Multispectral Images ◽  
Rx Detector

scholarly journals ESTIMATION OF THE ATTITUDE PERTURBANCE USING PARALLAX IMAGERY - APPLICATION TO ZY-3 SATELLITE

2015 ◽  
Vol II-3/W4 ◽  
pp. 279-283 ◽  
Author(s):  
Z. Ye ◽  
Y. Xu ◽  
F. Wang ◽  
S. Liu ◽  
X. Tang ◽  
...  
Keyword(s):  
Detection Method ◽  
Earth Observation ◽  
Multispectral Images ◽  
The Earth ◽  
Novel Approach ◽  
Earth Observation Satellite

The inflight stability of the earth observation satellite is a significant factor having an influence on the geometric performance of its imagery. The estimation of the attitude perturbance is therefore indispensable to spaceborne photogrammetry application. In this paper, an experiment using a short strip of multispectral images obtained from ZY-3 satellite is conducted. The detection method for attitude perturbance based on parallax observation is adopted, while a novel approach of estimating the attitude perturbance angles from the perturbance caused image displacements is also proposed and demonstrated. The estimated results indicate that the ZY-3 satellite was affected by considerable perturbances with distinctive frequencies during the flight of the investigated images, and attitude perturbances hava also undermined the geometric performance of the acquired imagery.

scholarly journals A JITTER DETECTION METHOD BASED ON THE INTEGRATION IMAGING MODEL

2020 ◽  
Vol V-3-2020 ◽  
pp. 709-715
Author(s):  
G. Ye ◽  
J. Pan ◽  
Y. Zhu ◽  
S. Jin
Keyword(s):  
Random Error ◽  
Detection Method ◽  
Image Space ◽  
Multispectral Images ◽  
Error Source ◽  
Image Degradation ◽  
Object Space ◽  
Imaging Model ◽  
The Relationship

Abstract. Satellite jitter is a random error source which leads to image degradation. This paper proposes a method to detect the time-variant jitter using multispectral images. In the method, multispectral images are adopted for their large overlap to obtain the parallax map. The imaging process is analyzed in details, and an integration imaging model is constructed, which takes fully into account the time-variant jitter property and builds the relationship between object space with image space. Besides, multispectral images of ZY-3 satellite were used for experiments, and results show that the presented method obtains the jitter curve with the error of amplitude, frequency and phase not more than 0.0591 px, 0.0006 Hz and 0.007 rad, respectively. Results demonstrate the performance of the presented method in jitter detection.

Solid-phase immunoelectron microscopy for rapid diagnosis of enteroviruses

1984 ◽  
Vol 42 ◽  
pp. 226-227 ◽  
Author(s):  
K. Pegg-Feige ◽  
F. W. Doane
Keyword(s):  
Electron Microscopy ◽  
Cell Culture ◽  
Immunoelectron Microscopy ◽  
Detection Method ◽  
Solid Phase ◽  
Protein A ◽  
Plant Viruses ◽  
Rapid Diagnosis ◽  
Virus Diagnosis ◽  
Antiviral Antibody

Immunoelectron microscopy (IEM) applied to rapid virus diagnosis offers a more sensitive detection method than direct electron microscopy (DEM), and can also be used to serotype viruses. One of several IEM techniques is that introduced by Derrick in 1972, in which antiviral antibody is attached to the support film of an EM specimen grid. Originally developed for plant viruses, it has recently been applied to several animal viruses, especially rotaviruses. We have investigated the use of this solid phase IEM technique (SPIEM) in detecting and identifying enteroviruses (in the form of crude cell culture isolates), and have compared it with a modified “SPIEM-SPA” method in which grids are coated with protein A from Staphylococcus aureus prior to exposure to antiserum.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

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