Lossy-to-lossless block-based compression of hyperspectral volumetric data

An embedded, block-based, wavelet transform coding algorithm of low complexity is proposed. Three-dimensional set partitioned embedded block (3D-SPECK) efficiently encodes, hyperspectral volumetric image data by exploiting the dependencies in all dimensions. Integer wavelet transform is applied to enable lossy and lossless decompression from the same bit stream. We demonstrate that 3D-SPECK, a wavelet domain algorithm, like other time domain algorithms, can preserve spectral profiles well. Airborne visible infrared imaging spectrometer (AVIRIS) imagery is used to test the proposed algorithm. Results show that 3D-SPECK, in addition to being very flexible, retains all the desirable features of compared state-of-the-art algorithms and is highly competitive to 3D-SPIHT and better than JPEG2000 multi-component in compression efficiency.