Four-Dimensional Wavelet Compression of 4-D Medical Images Using Scalable 4-D SBHP

This paper proposes a low-complexity wavelet-based method for progressive lossy-to-lossless compression of four dimensional (4-D) medical images. The subband block hierarchal partitioning (SBHP) algorithm is modified and extended to four dimensions, and applied to every code block independently. The resultant algorithm, 4D-SBHP, efficiently encodes 4D image data by the exploitation of the dependencies in all dimensions, while enabling progressive SNR and resolution decompression. The resolution scalable and lossy-to-lossless performances are empirically investigated. The experimental results show that our 4-D scheme achieves better compression performance on 4-D medical images when compared with 3-D volumetric compression schemes