The goal for this work is to evaluate the impact of utilizing shorter wavelet filters in the CCSDS standard for lossy and lossless image compression. Another constraint considered was the existence of symmetry in the filters. That approach was desired to maintain the symmetric extension compatibility of the filter banks. Even though this strategy works well for oat wavelets, it is not always the case for their integer approximations. The periodic extension was utilized whenever symmetric extension was not applicable. Even though the latter outperforms the former, for fair comparison the symmetric extension compatible integer-to-integer wavelet approximations were evaluated under both extensions.
The evaluation methods adopted were bit rate (bpp), PSNR and the number of operations required by each wavelet transforms. All these results were compared against the ones obtained utilizing the standard CCSDS with 9/7 filter banks, for lossy and lossless compression.
The tests were performed over tallies (512x512) of raw remote sensing images from CBERS-2B (China-Brazil Earth Resources Satellites) captured from its high resolution CCD camera. These images were cordially made available by INPE (National Institute for Space Research) in Brazil. For the CCSDS implementation, it was utilized the source code developed by Hongqiang Wang from the Electrical Department at Nebraska-Lincoln University, applying the appropriate changes on the wavelet transform.
For lossy compression, the results have shown that the filter bank built from the Deslauriers-Dubuc scaling function, with respectively 2 and 4 vanishing moments on the synthesis and analysis banks, presented not only a reduction of 21% in the number of operations required, but also a performance on par with the 9/7 filter bank. In the lossless case, the biorthogonal Cohen-Daubechies-Feauveau with 2 vanishing moments presented a performance close to the 9/7 integer approximation of the CCSDS, with the number of operations reduced by 1/3.