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Research and Application of Remote Sensing Image Subblock and Classification

Author: LiuTao
Tutor: SunZhongLin
School: Shandong University of Science and Technology
Course: Computer Software and Theory
Keywords: Remote sensing image Classification Distributed computing Speedup
CLC: TP751
Type: Master's thesis
Year: 2010
Downloads: 146
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Abstract


Remote sensing image classification is an important aspect of the remote sensing image processing , has been widely used in the marine , agriculture , geology , meteorology , environmental , military and other fields . With the development of satellite sensor technology and data communications technology , remote sensing technology has entered a dynamic , real-time , accurate and a new era of remote sensing image data is growing . On one hand, the increase of the amount of data led to the remote sensing image classification need to spend a lot of time . On the other hand , a lot of computing resources in the LAN is idle. How at the same time does not affect the classification accuracy , take full advantage of network computing resources , remote sensing image classification has become a hot topic of research today . Distributed computing as a new kind of technology , you can quickly solve large and complex computing problems , and provide a new direction for the development of the technology of remote sensing image classification . From the application point of view , the paper analyzes the problems in the current remote sensing image classification techniques , pointed out the need for the introduction of distributed computing in remote sensing image classification . Calculated for remote sensing image classification process a long time , the problem of low efficiency , papers introduction of distributed computing technology on remote sensing image classification study class library for distributed computing MPI Research and Application , combine the messaging mechanism LAN , does not change the condition of the hardware environment to achieve high performance distributed computing . On the basis of the analysis and comparison of the speedup and acceleration efficiency factors , in order to achieve the maximum speedup , the paper presents two block algorithm for remote sensing image load balancing priority priority block block algorithm and efficiency algorithm. Through the comparison of the two algorithms speedup , the paper illustrates the application environment and the advantages and disadvantages of the two algorithms . The papers of the sub - blocks of the remote sensing image classification prototype design and implementation on the basis of the MPI library . Through the analysis of sub- blocks of the remote sensing image classification prototype , the prototype system is divided into a number of functional modules , described in detail the function of each module , and C programming . Sub- blocks of the remote sensing image classification prototype to increase image block transmission time at the expense complex calculations on a computer distribution relatively independent compute nodes so that the calculation is done ahead of time .

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CLC: > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods
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