Application of PCA Numalgorithm in Remote Sensing Image Processing

Hong Dai(School of Computer and Information Engineering, Shanghai Second Polytechnic University)

Abstract

A numerical algorithm of principal component analysis (PCA) is proposed and its application in remote sensing image processing is introduced:(1) Multispectral image compression; (2) Multi-spectral image noise cancellation; (3) Information fusion of multi-spectral images and spot panchromatic images. The software experiments verify and evaluate the effectiveness and accuracy of the proposed algorithm.

Keywords

PCA numerical algorithm；Remote sensing image processing；Multi-spectral image

References

Wei, Y.Ch., Tang, G.A., Yang, X., et al., 2001. Remote sensing digital Image processing tutorial. Beijing: Science Press. pp. 1-30.

Gonzalez, R.C., Woods, R.E., 2003. Digital image processing (Version 2). Beijing: Electronic Industry Press. pp. 550-560.

Zhang, J., Lu, Y.H., Liu, Q.Y., 2006. Application of an improved embedded wavelet algorithm in remote sensing image compression. Microcomputer Information. (3-2), 79-81.

Zhong, W.B., Ning, Sh.N., Jin, S.Z., et al., 2004. Remote sensing imaging noise analysis and the PCNNbased filtering method. Journal of Coal. (4), 18-421.

Gao, Sh.Ch., 2006. VISUAL C + + practice and improvement: Digital image processing and engineering application. Beijing: China Railway Press. pp. 326-342.

DOI: http://dx.doi.org/10.26549/met.v7i1.12317