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Analysis‐aware microscopy video compression
Author(s) -
Shao Chong,
Cribb Jeremy,
Osborne Lukas D.,
O'Brien E. Timothy,
Superfine Richard,
MayerPatel Ketan,
Taylor Russell M.
Publication year - 2018
Publication title -
microscopy research and technique
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 118
eISSN - 1097-0029
pISSN - 1059-910X
DOI - 10.1002/jemt.23025
Subject(s) - video microscopy , microscopy , computer science , data compression , flexibility (engineering) , compression (physics) , computer vision , tracking (education) , artificial intelligence , algorithm , optics , materials science , mathematics , statistics , composite material , physics , psychology , pedagogy , biology , microbiology and biotechnology
This article introduces an analysis‐aware microscopy video compression method designed for microscopy videos that are consumed by analysis algorithms rather than by the human visual system. We define the quality of a microscopy video based on the level of preservation of analysis results. We evaluated our method with a bead tracking analysis program. For the same error level in the analysis result, our method can achieve 1,000× compression on certain test microscopy videos. Compared with a previous technique that yields exactly the exact same results by analysis algorithms, our method gives more flexibility for a user to control the quality. A modification to the new method also provides faster compression speed.