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Remote Sensing Science

Remote Sensing Science is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of remote sensing science and technology. The main focus of the journal is the academic papers and comments of latest improvement in the fields of basic theory, technology development and application of remote sensing science, report of latest research result, aiming at providing a good communication platform to tran... [More] Remote Sensing Science is an international comprehensive professional academic journal of Ivy Publisher, concerning the development of remote sensing science and technology. The main focus of the journal is the academic papers and comments of latest improvement in the fields of basic theory, technology development and application of remote sensing science, report of latest research result, aiming at providing a good communication platform to transfer, share and discuss the theoretical and technical development of remote-sensing theory development for professionals, scholars, researchers and administrative staffs in this field, reflecting the academic front level, promote academic change and seize the theory, practice front line, research level and development direction of remote sensing science.

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ISSN Print:2329-8138

ISSN Online:2329-8146

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Paper Infomation

Parallel Computing Reasearch of Normalized Difference Vegetation Index Based on OpenMP and OpenCV

Full Text(PDF, 203KB)

Author: Xianyu Zuo, Dongdong Shang, Beibei Li, Minghao Xiong, Xiangzhi Huang

Abstract: The study of normalized difference vegetation index (NDVI) is the main field of remote sensing application, and also an important issue in the field of remote sensing. With the progress of remote sensing in China, the high resolution satellite developed by ourselves has been launched in succession, which has accelerated and expanded the application range of high resolution satellite images produces a large number of remote sensing images. High resolution remote sensing images produced by satellites every day also show exponential growth, reaching the order for Terabyte (TB) even Petabyte (PB) level. However, the traditional serial vegetation index extraction algorithm can’t extract the vegetation index from these massive remote sensing data in time and effectively. Based on this, this paper will use the normalized vegetation index (NDVI) algorithm as an example, Optimization of the NDVI algorithm, which based on the support of the high performance research platform and parallel computing technology, achieved the parallel computation method of NDVI fast extraction through C++ programming language library function calling OpenMP and OpenCV and verified the validity of NDVI parallel extraction algorithm by GF-1 data.

Keywords: Normalized Difference Vegetation Index, NDVI Algorithm, Parallel Computing, OpenMP, OpenCV

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