We investigate conditions for unique signal recovery based on sparse and cosparse signal models from few tomographic projections.Although certain industrial tomographic sensors do not fulfil typical Compressed Sensing conditions,we show that the transition from non-recovery to recovery is sharp for specific sparse images.The signal class covered by both sparse and cosparse models seems broad enough to cover relevant industrial applications of non-standard tomography,like particle image velocimetry and contactless quality inspection.