  Light-field fluorescence microscopy (LFM) is a powerful elegant compact
method for long-term high-speed imaging of complex biological systems, such as
neuron activities and rapid movements of organelles. LFM experiments typically
generate terabytes image data and require a huge number of storage space. Some
lossy compression algorithms have been proposed recently with good compression
performance. However, since the specimen usually only tolerates low power
density illumination for long-term imaging with low phototoxicity, the image
signal-to-noise ratio (SNR) is relative-ly low, which will cause the loss of
some efficient position or intensity information by using such lossy
compression al-gorithms. Here, we propose a phase-space continuity enhanced
bzip2 (PC-bzip2) lossless compression method for LFM data as a high efficiency
and open-source tool, which combines GPU-based fast entropy judgement and
multi-core-CPU-based high-speed lossless compression. Our proposed method
achieves almost 10% compression ratio improvement while keeping the capability
of high-speed compression, compared with original bzip2. We evaluated our
method on fluorescence beads data and fluorescence staining cells data with
different SNRs. Moreover, by introducing the temporal continuity, our method
shows the superior compression ratio on time series data of zebrafish blood
vessels.
