scholarly journals Research on Image Fusion Algorithm Based on Nonsubsampled Shear Wave Transform and Principal Component Analysis

2022 ◽  
Vol 2146 (1) ◽  
pp. 012025
Author(s):  
Huiying Jia
Keyword(s):  
Principal Component Analysis ◽  
Computer Technology ◽  
Remote Monitoring ◽  
Principal Component ◽  
Development Trend ◽  
Fusion Algorithm ◽  
Monitoring Technology ◽  
Related Research ◽  
Development Status ◽  
Design And Implementation

Abstract With the development of network remote monitoring technology, its application in all walks of life has become more and more extensive. The application of remote monitoring technology makes the development of all walks of life more intelligent and informatized. This paper analyzes the development status of remote monitoring technology, and studies the design and implementation of remote network monitoring system based on computer technology. It also conducts related research on the future development trend of remote monitoring technology.

Panoramic Image System Design in the Nearly Dark Environment

2013 ◽  
Vol 464 ◽  
pp. 304-309 ◽  
Author(s):  
Geng Chen ◽  
Qing Li ◽  
Hao Zhang
Keyword(s):  
Principal Component Analysis ◽  
Imaging System ◽  
Principal Component ◽  
Image Mosaic ◽  
Panoramic Image ◽  
Image System ◽  
Fusion Algorithm ◽  
Canny Operator ◽  
Image Edge ◽  
Wireless Module

Aiming at the need of borehole and ruins exploration in the nearly dark environment, a Panoramic Image System is proposed in this paper. consisting of a reciprocating motor, a steering gear with complete rotation, a miniature camera, a depth transducer and radio frequency wireless module. The camera was pushed to the specified location of the pipe by the motor and then the steering gear was rotated for panorama image acquisition. In order to achieve a seamless panoramic image without distortion, a fusion algorithm based on Principal Component Analysis (PCA) and an image mosaic algorithm for image edge extracting based on Canny operator were proposed. The imaging system has good usability and applicability.

Study of the Cluster Analysis Algorithm for Radio Advertising

2015 ◽  
Vol 713-715 ◽  
pp. 1935-1938
Author(s):  
Ji Hong Liu ◽  
Yu Tao Fu ◽  
Qi Zhang ◽  
Yu Ting Geng
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Algorithm ◽  
Design And Implementation ◽  
Key Technologies ◽  
Audio Data

Some key technologies for clustering the radio advertising are introduced firstly. Then the design and implementation of the system are presented. The system analyzes the cluster characters for radio advertising by principal component analysis. It could be used to capture the radio ads’ time slots. This system shows a way to analyze audio data, and could be used to classify and identify different audio ads. Therefore, it has a wonderful application prospect.

Development of Bridge Concealment Engineering State Detection Technology

2014 ◽  
Vol 926-930 ◽  
pp. 541-544
Author(s):  
Yi Zheng ◽  
Ke Chao Zhang ◽  
Jian Zhang Chen
Keyword(s):  
Technology Development ◽  
Development Trend ◽  
Foreground Detection ◽  
Monitoring Technology ◽  
Development Status ◽  
Detection Technology ◽  
State Detection ◽  
Engineering State

Main detection and monitoring technology of bridges construction concealment engineering were carried out investigation and analysis. The use of concealed engineering inspection technology, monitoring technology were overviewed and analyzed. The development status of detection, monitoring technology at present reviewed and analyzed. Detection technology parameters on the internal prestress were compared. Technology development trend and foreground detection of concealed engineering were presented. Key words:bridge structure、concealed engineering、detection technology、monitoring technology、stress statement

scholarly journals Energy Investment Potential and Strategic Layout in Countries along the “Belt and Road” Based on Principal Component Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiao-Feng Xu ◽  
Min Liu ◽  
Li Ma ◽  
Yang Li
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Development Trend ◽  
Assessment System ◽  
Energy Investment ◽  
Five Dimensions ◽  
Investment Structure ◽  
Belt And Road ◽  
The Belt And Road

It is important for energy enterprises to research on the investment potential of the energy markets in countries along the “Belt and Road,” which can help them optimize the regional investment structure, reduce investment risks, and conform to the development trend of “going global.” Therefore, we construct an investment potential assessment system of 29 indexes including five dimensions: politics, economy, society, energy, and cooperation and assess energy investment potential of 48 sample countries along the “Belt and Road” using principal component analysis to provide reference meanings for energy enterprises. The results show that the assessment results of investment potential are affected by a combination of multiple indexes. In addition, compared with Central Asia and South Asia, which have weak economic foundations and greater political and legal risks, the investment potential of Central and Eastern Europe and some emerging economies in Southeast Asia is higher.

scholarly journals Image Fusion Algorithm Based on Contourlet Transform and PCNN for Detecting Obstacles in Forests

2015 ◽  
Vol 15 (1) ◽  
pp. 116-125 ◽  
Author(s):  
Zheng Yu ◽  
Lei Yan ◽  
Ning Han ◽  
Jinhao Liu
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Wavelet Transform ◽  
Image Fusion ◽  
Principal Component ◽  
Experimental Results ◽  
Contourlet Transform ◽  
Detection Accuracy ◽  
Fusion Algorithm ◽  
Infrared Thermal Images

Abstract In this paper the image fusion algorithm based on Contourlet transform and Pulse Coupled Neural Network (PCNN) was proposed to improve the performance of the image fusion in the detection accuracy of obstacles in forests. At the same time, the wavelet transform and the Principal Component Analysis (PCA) were simulated for comparison with the proposed algorithm. Then visible and infrared thermal images were collected in a forest. The experimental results have shown that the fused images using the method proposed provided a better understanding of the reality, enhanced images’ clarity and eliminated factors which provided shelters for targets.

A Time-Series Trend Forecast Method Based on Principal Component Analysis

2012 ◽  
Vol 472-475 ◽  
pp. 2984-2987
Author(s):  
Shu Di Wei ◽  
Hui Huang Zhao
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Image Data ◽  
Principal Component ◽  
Component Analysis ◽  
Series Data ◽  
Text Data ◽  
Related Research ◽  
Time Series Method ◽  
Scan Data

The time-series is the collection of chronological varying numerical ordered by time. It has a wide existence of image data, text data, hand-written data and the brain scan data patterns. The present research of time-series concentrates on series data transformation, similarity search, forecast, classification, clustering and Visualization etc. Furthermore the trend forecast of time-series is the major basis of other related research. This paper analyses the existing time-series forecasting methods and puts forward a new time-series method based on principal component analysis. The example tests the validity of the method of other related research.

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