  We present a method for the recovery of compressively sensed acoustic fields
using patterned, instead of point-by-point, detection. From a limited number of
such compressed measurements, we propose to reconstruct the field on the sensor
plane in each time step independently assuming its sparsity in a Curvelet
frame. A modification of the Curvelet frame is proposed to account for the
smoothing effects of data acquisition and motivated by a frequency domain model
for photoacoustic tomography. An ADMM type algorithm, SALSA, is used to recover
the pointwise data in each individual time step from the patterned
measurements. For photoacoustic applications, the photoacoustic image of the
initial pressure is reconstructed using time reversal in ${\bf k}$-Wave
Toolbox.
