Share Email Print
cover

Proceedings Paper

MAXAD distortion minimization for wavelet compression of remote sensing data
Author(s): Alin Alecu; Adrian Munteanu; Peter Schelkens; Jan P.H. Cornelis; Steven Dewitte
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In the context of compression of high resolution multi-spectral satellite image data consisting of radiances and top-of-the-atmosphere fluxes, it is vital that image calibration characteristics (luminance, radiance) must be preserved within certain limits in lossy image compression. Though existing compression schemes (SPIHT, JPEG2000, SQP) give good results as far as minimization of the global PSNR error is concerned, they fail to guarantee a maximum local error. With respect to this, we introduce a new image compression scheme, which guarantees a MAXAD distortion, defined as the maximum absolute difference between original pixel values and reconstructed pixel values. In terms of defining the Lagrangian optimization problem, this reflects in minimization of the rate given the MAXAD distortion. Our approach thus uses the l-infinite distortion measure, which is applied to the lifting scheme implementation of the 9-7 floating point Cohen-Daubechies-Feauveau (CDF) filter. Scalar quantizers, optimal in the D-R sense, are derived for every subband, by solving a global optimization problem that guarantees a user-defined MAXAD. The optimization problem has been defined and solved for the case of the 9-7 filter, and we show that our approach is valid and may be applied to any finite wavelet filters synthesized via lifting. The experimental assessment of our codec shows that our technique provides excellent results in applications such as those for remote sensing, in which reconstruction of image calibration characteristics within a tolerable local error (MAXAD) is perceived as being of crucial importance compared to obtaining an acceptable global error (PSNR), as is the case of existing quantizer design techniques.

Paper Details

Date Published: 5 December 2001
PDF: 12 pages
Proc. SPIE 4475, Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications, (5 December 2001); doi: 10.1117/12.449577
Show Author Affiliations
Alin Alecu, Vrije Univ. Brussel (Belgium)
Adrian Munteanu, Vrije Univ. Brussel (Belgium)
Peter Schelkens, Vrije Univ. Brussel (Belgium)
Jan P.H. Cornelis, Vrije Univ. Brussel (Belgium)
Steven Dewitte, Royal Meteorological Institute Belgium (Belgium)


Published in SPIE Proceedings Vol. 4475:
Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications
Mark S. Schmalz, Editor(s)

© SPIE. Terms of Use
Back to Top