  We describe an advanced image reconstruction algorithm for pseudothermal
ghost imaging, reducing the number of measurements required for image recovery
by an order of magnitude. The algorithm is based on compressed sensing, a
technique that enables the reconstruction of an N-pixel image from much less
than N measurements. We demonstrate the algorithm using experimental data from
a pseudothermal ghost-imaging setup. The algorithm can be applied to data taken
from past pseudothermal ghost-imaging experiments, improving the
reconstruction's quality.
