Lossless compression of 3D MRI and CT data
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abstract
We propose a conceptually simple method for lossless compression of medical image and volume data. The method can be divided into three steps: the input data is decomposed into several subbands with the help of nonlinear lifting filters, the resulting subbands are block-sorted according to a method suggested by Burrows and Wheeler, and the redundancy is removed with the help of an adaptive arithmetic coder. Moreover, we suggest a new method to implement (non-linear) lifting filters. We describe these filters with the help of a small filter description language, which is compiled into a shared object file and dynamically loaded at run time. The source code of the program is freely available for testing purposes.
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Wavelet Applications in Signal and Imaging Processing VI