  Optical wide-field surveys with a high cadence are expected to create a new
field of astronomy, so-called "movie astronomy," in the near future. The amount
of data of the observations will be huge, and hence efficient data compression
will be indispensable. Here we propose a low-rank matrix approximation with
sparse matrix decomposition as a promising solution to reduce the data size
effectively, while preserving sufficient scientific information. We apply one
of the methods to the movie data obtained with the prototype model of the
Tomo-e Gozen mounted on the 1.0-m Schmidt telescope of Kiso Observatory. Once
the full-scale observation of the Tomo-e Gozen commences, it will generate ~30
TB of data per night. We demonstrate that the data are compressed by a factor
of about 10 in size without losing transient events like optical short
transient point-sources and meteors. The intensity of point sources can be
recovered from the compressed data. The processing runs sufficiently fast,
compared with the expected data-acquisition rate in the actual observing runs.
