title: Analysis-preserving video microscopy compression via correlation and mathematical morphology.
abstract: The large amount video data produced by multi-channel, high-resolution microscopy system drives the need for a new high-performance domain-specific video compression technique. We describe a novel compression method for video microscopy data. The method is based on Pearson's correlation and mathematical morphology. The method makes use of the point-spread function (PSF) in the microscopy video acquisition phase. We compare our method to other lossless compression methods and to lossy JPEG, JPEG2000, and H.264 compression for various kinds of video microscopy data including fluorescence video and brightfield video. We find that for certain data sets, the new method compresses much better than lossless compression with no impact on analysis results. It achieved a best compressed size of 0.77% of the original size, 25× smaller than the best lossless technique (which yields 20% for the same video). The compressed size scales with the video's scientific data content. Further testing showed that existing lossy algorithms greatly impacted data analysis at similar compression sizes.
authors.affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Chong
authors.initials: C
authors.lastname: Shao
authors.affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Alfred
authors.initials: A
authors.lastname: Zhong
authors.affiliation: Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Cribb
authors.affiliation: Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Lukas D
authors.initials: LD
authors.lastname: Osborne
authors.affiliation: Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: E Timothy
authors.initials: ET
authors.lastname: O'Brien
authors.affiliation: Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Richard
authors.initials: R
authors.lastname: Superfine
authors.affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Ketan
authors.initials: K
authors.lastname: Mayer-Patel
authors.affiliation: Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
authors.forename: Russell M
authors.initials: RM
authors.lastname: Taylor
keywords: biomedical image processing; data compression; image analysis