An LCT-wavelet based algorithms for data compression

We present an algorithm that compresses two-dimensional data arrays, which are piece-wise smooth in one direction and have oscillatory events in the other direction. Seismic and hyperspectral data have this mixed structure. The transform part of the compression process is an algorithm that combines wavelet and the local cosine transform (LCT). The quantization and the entropy coding parts in the compression process were taken from the SPIHT codec. To efficiently apply the SPIHT codec to a mixed coefficients array, reordering of the LCT coefficients takes place. When oscillating events are present in different directions as in fingerprints or when the image comprises a fine texture, the 2D LCT with reordering of coefficients is applied. These algorithms outperform algorithms that are solely based on the 2D wavelet transforms and SPIHT coding including JPEG2000 compression standard. The algorithms retain fine oscillating events including texture even at a low bitrate. Its compression capabilities are also demonstrated on multimedia images that have a fine texture. The wavelet part in the mixed transform of the hybrid algorithm utilizes the library of Butterworth wavelet transforms that outperforms the 9/7 biorthogonal wavelet library.