MODIS image compression based on JPEG2000

Data compression is used operationally to reduce bandwidth and storage requirements. JPEG2000 is the famous compression standard for still image coding. A study is presented for the lossless and lossy compression of MODIS image based on JPEG2000. We introduced the characteristic of MODIS data firstly and used some compression methods for the data. Experiments showed for lossless compression JPEG2000 outperforms the universal compression software WINZIP and for lossy compression JPEG2000 with the non-reversible filter outperforms all other algorithms at all bitrate.

[1]  Arto Kaarna,et al.  Improved back end for integer PCA and wavelet transforms for lossless compression of multispectral images , 2002, Object recognition supported by user interaction for service robots.

[2]  Arto Kaarna.  Integer PCA and wavelet transforms for multispectral image compression , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[3]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..

[4]  Touradj Ebrahimi,et al.  The JPEG2000 still image coding system: an overview , 2000, IEEE Trans. Consumer Electron..

[5]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

[6]  Jarno Mielikäinen,et al.  Improved vector quantization for lossless compression of AVIRIS images , 2002, 2002 11th European Signal Processing Conference.

[7]  S. Srinivasan,et al.  Eigen wavelet: hyperspectral image compression algorithm , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[8]  R. E. Roger,et al.  Lossless compression of AVIRIS images , 1996, IEEE Trans. Image Process..

[9]  John F. Arnold,et al.  The lossless compression of AVIRIS images by vector quantization , 1997, IEEE Trans. Geosci. Remote. Sens..