Remote sensing image classification algorithm based on image activity measure for image compression applications

Xin Tian; Lin Wu; Tao Li; Cheng-Yi Xiong; Song Li

doi:10.1117/12.2031389

26 October 2013 Remote sensing image classification algorithm based on image activity measure for image compression applications

Xin Tian, Lin Wu, Tao Li, Cheng-Yi Xiong, Song Li

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Proceedings Volume 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis; 89170U (2013) https://doi.org/10.1117/12.2031389
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

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.

Citation Download Citation

Xin Tian, Lin Wu, Tao Li, Cheng-Yi Xiong, and Song Li "Remote sensing image classification algorithm based on image activity measure for image compression applications", Proc. SPIE 8917, MIPPR 2013: Multispectral Image Acquisition, Processing, and Analysis, 89170U (26 October 2013); https://doi.org/10.1117/12.2031389

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KEYWORDS

Image compression

Image classification

Remote sensing

JPEG2000

Data transmission

Distortion

Quantization

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