MAXAD distortion minimization for wavelet compression of remote sensing data

Alin Alecu; Adrian Munteanu; Peter Schelkens; Jan P.H. Cornelis; Steven Dewitte

doi:10.1117/12.449577

5 December 2001 MAXAD distortion minimization for wavelet compression of remote sensing data

Alin Alecu, Adrian Munteanu, Peter Schelkens, Jan P.H. Cornelis, Steven Dewitte

Proceedings Volume 4475, Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications; (2001) https://doi.org/10.1117/12.449577
Event: International Symposium on Optical Science and Technology, 2001, San Diego, CA, United States

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.

Citation Download Citation

Alin Alecu, Adrian Munteanu, Peter Schelkens, Jan P.H. Cornelis, and Steven Dewitte "MAXAD distortion minimization for wavelet compression of remote sensing data", Proc. SPIE 4475, Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications, (5 December 2001); https://doi.org/10.1117/12.449577

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