Current density reconstruction with multi-scale grid approach

2005 ◽  
Author(s):  
J.-M. Han ◽  
I.B. Lee ◽  
J.H. Hahm ◽  
Y.J. Kim ◽  
K.S. Park
Keyword(s):  
Current Density ◽  
Multi Scale ◽  
Grid Approach ◽  
Scale Grid

scholarly journals Construction of multi-scale grid for massive land survey data

2020 ◽  
Vol 206 ◽  
pp. 03018
Author(s):  
Jia Zhang ◽  
Xiulian Wang ◽  
Xiaotong Zhang ◽  
Xiaofei Bai ◽  
Qiang Chen
Keyword(s):  
Information Integration ◽  
Data Model ◽  
Spatiotemporal Data ◽  
Distributed Data ◽  
Data Organization ◽  
Vector Data ◽  
Grid Data ◽  
Geospatial Information ◽  
Multi Scale ◽  
Scale Grid

In the face of ever-growing and complex massive multi-source spatiotemporal data, the traditional vector data model is increasingly difficult to meet the needs of efficient data organization, management, calculation and analysis. Based on the simple and widely used geographic grid data organization model, this paper designs a technical method to convert vector data into multi-scale grid data, establishes a unified, standardized and seamless land spatial grid data model, and analyses the area accuracy of multi-scale grid data. Practice shows that the model can better meet the needs of multi-scale geospatial information integration and analysis, and it is easy to carry out distributed data processing, which provides technical support for the efficient organization, fusion and analysis of spatiotemporal data.

227 Spatial development and decay characteristic of turbulence generated by fractal, classical, multi-scale grid

2016 ◽  
Vol 2016.65 (0) ◽  
pp. _227-1_-_227-2_
Author(s):  
Teppei SAIKI ◽  
Koji NAGATA ◽  
Yasuhiko SAKAI ◽  
Yasumasa ITO ◽  
Koji IWANO
Keyword(s):  
Spatial Development ◽  
Decay Characteristic ◽  
Multi Scale ◽  
Scale Grid

scholarly journals Defocused image restoration method based on micro-nano scale

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yongjun Liu ◽  
Qiuyu Wu ◽  
Mingxin Zhang ◽  
Yi Wang
Keyword(s):  
Image Restoration ◽  
Enhancement Effect ◽  
Multi Scale ◽  
Nano Scale ◽  
Adaptive Noise ◽  
Restoration Method ◽  
Defocused Image ◽  
Optical Defocus ◽  
Scale Grid

An image adaptive noise reduction enhancement algorithm based on NSCT is proposed to perform image restoration preprocessing on the defocused image obtained under the microscope. Defocused images acquired under micro-nano scale optical microscopy, usually with inconspicuous details, edges and contours, affect the accuracy of subsequent observation tasks. Due to its multi-scale and multi-directionality, the NSCT transform has superior transform functions and can obtain more textures and edges of images. Combined with the characteristics of micro-nanoscale optical defocus images, the NSCT inverse transform is performed on all sub-bands to reconstruct the image. Finally, the experimental results of the standard 500nm scale grid, conductive probe and triangular probe show that the proposed algorithm has a better image enhancement effect and significantly improves the quality of out-of-focus images.

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