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Proceedings Paper

Remote sensing image classification algorithm based on image activity measure for image compression applications
Author(s): Xin Tian; Lin Wu; Tao Li; Cheng-Yi Xiong; Song Li
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Paper Abstract

A remote sensing image classification algorithm based on image activity measure is proposed, which is used for adaptive image compression applications. The image activity measure has been studied and the support vector machine(SVM) is introduced. Then, the relationship between the image activity measure and the distortion caused by quantization is discussed in our image compression experiments (JPEG2000, CCSDS and SPIHT). Another two image activity measures are proposed as well. Then a feature vector is constructed by image activity measures in order to describe the image compression features of different images. The test images are classified by support vector machine classifier. The effectiveness of the proposed algorithm has been tested using an image data set, which demonstrates the advantage of the proposed algorithm.

Paper Details

Date Published: 26 October 2013
PDF: 5 pages
Proc. SPIE 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis, 89170U (26 October 2013); doi: 10.1117/12.2031389
Show Author Affiliations
Xin Tian, Wuhan Univ. (China)
Lin Wu, Institute of Geodesy and Geophysics (China)
Tao Li, Huazhong Univ. of Science and Technology (China)
Cheng-Yi Xiong, South-Central Univ. for Nationalities (China)
Song Li, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 8917:
MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Jianguo Liu, Editor(s)

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