scholarly journals Illustrations Segmentation in Digitized Documents Using Local Correlation Features

2014 ◽  
Vol 38 ◽  
pp. 76-83 ◽  
Author(s):  
Dalia Coppi ◽  
Costantino Grana ◽  
Rita Cucchiara
Keyword(s):  
Local Correlation ◽  
Digitized Documents

Detection of the Structural Failing Point Using Correlation and Local Correlation Analysis

2020 ◽  
Author(s):  
Hyounkyun Oh ◽  
Younghan Jung ◽  
Junyong Ahn ◽  
Sujin Kim ◽  
M. Myung Jeong
Keyword(s):  
Correlation Analysis ◽  
Local Correlation

scholarly journals Rock Location and Property Analysis of Lunar Regolith at Chang’E-4 Landing Site Based on Local Correlation and Semblance Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Hanjie Song ◽  
Chao Li ◽  
Jinhai Zhang ◽  
Xing Wu ◽  
Yang Liu ◽  
...  
Keyword(s):  
Electromagnetic Waves ◽  
Lunar Regolith ◽  
Landing Site ◽  
Rock Properties ◽  
The Moon ◽  
Local Correlation ◽  
Near Surface ◽  
Property Analysis ◽  
Stratigraphic Division ◽  
Formation And Evolution

The Lunar Penetrating Radar (LPR) onboard the Yutu-2 rover from China’s Chang’E-4 (CE-4) mission is used to probe the subsurface structure and the near-surface stratigraphic structure of the lunar regolith on the farside of the Moon. Structural analysis of regolith could provide abundant information on the formation and evolution of the Moon, in which the rock location and property analysis are the key procedures during the interpretation of LPR data. The subsurface velocity of electromagnetic waves is a vital parameter for stratigraphic division, rock location estimates, and calculating the rock properties in the interpretation of LPR data. In this paper, we propose a procedure that combines the regolith rock extraction technique based on local correlation between the two sets of LPR high-frequency channel data and the common offset semblance analysis to determine the velocity from LPR diffraction hyperbola. We consider the heterogeneity of the regolith and derive the relative permittivity distribution based on the rock extraction and semblance analysis. The numerical simulation results show that the procedure is able to obtain the high-precision position and properties of the rock. Furthermore, we apply this procedure to CE-4 LPR data and obtain preferable estimations of the rock locations and the properties of the lunar subsurface regolith.

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

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