Distributed imaging using an array of compressive cameras

We describe a distributed computational imaging system that employs an array of feature specific sensors, also known as compressive imagers, to directly measure the linear projections of an object. Two different schemes for implementing these non-imaging sensors are discussed. We consider the task of object reconstruction and quantify the fidelity of reconstruction using the root mean squared error (RMSE) metric. We also study the lifetime of such a distributed sensor network. The sources of energy consumption in a distributed feature specific imaging (DFSI) system are discussed and compared with those in a distributed conventional imaging (DCI) system. A DFSI system consisting of 20 imagers collecting DCT, Hadamard, or PCA features has a lifetime of 4.8× that of the DCI system when the noise level is 20% and the reconstruction RMSE requirement is 6%. To validate the simulation results we emulate a distributed computational imaging system using an experimental setup consisting of an array of conventional cameras.