Optimal linear prediction of ordered bands and lifting wavelet transform applied to lossless compression of MODIS image

Xubing Zhang; Zequn Guan; Xin Yu

doi:10.1117/12.774815

14 November 2007 Optimal linear prediction of ordered bands and lifting wavelet transform applied to lossless compression of MODIS image

Xubing Zhang, Zequn Guan, Xin Yu

Author Affiliations +

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67905F (2007) https://doi.org/10.1117/12.774815
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

The enormous volumes and valuable applications of MODIS (Moderate Resolution Imaging Spectroradiometer) multi-spectral images make it need to be compressed losslessly with effective method. To solve this problem, the optimal linear prediction and band ordering are adopted here to exploit abundant spectral redundancy, lifting wavelet transform and SPIHT algorithm are used to eliminate the spatial redundancy of MODIS data. The optimal inter-band prediction sequence is specified by band ordering, and except the first band, only residual error images of other bands need to be encoded after band prediction. To avoid information loss, the optimal linear predictor is improved by rounding the prediction coefficients into integers, and D5/3 lifting wavelet is used to implement integer-to-integer wavelet transform of the band image, which also accelerate the compression. Finally, some lossless compression methods such as "WinRAR", "3DSPIHT" are compared with this compression method, and the experimental results show that our method has more compression capability.

Citation Download Citation

Xubing Zhang, Zequn Guan, and Xin Yu "Optimal linear prediction of ordered bands and lifting wavelet transform applied to lossless compression of MODIS image", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67905F (14 November 2007); https://doi.org/10.1117/12.774815

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available