Two instance of CS Hardware today:

Compressive Imaging and Characterization of Sparse Light Deflection Maps by Prasad Sudhakar, Laurent Jacques, Xavier Dubois, Philippe Antoine, Luc Joannes

Light rays incident on a transparent object of uniform refractive index undergo deflections, which uniquely characterize the surface geometry of the object. Associated with each point on the surface is a deflection map which describes the pattern of deflections in various directions and it tends to be sparse when the object surface is smooth. This article presents a novel method to efficiently acquire and reconstruct sparse deflection maps using the framework of Compressed Sensing (CS). To this end, we use a particular implementation of schlieren deflectometer, which provides linear measurements of the underlying maps via optical comparison with programmable spatial light modulation patterns. To optimize the number of measurements needed to recover the map, we base the design of modulation patterns on the principle of spread spectrum CS. We formulate the map reconstruction task as a linear inverse problem and provide a complete characterization of the proposed method, both on simulated data and experimental deflectometric data. The reconstruction techniques are designed to incorporate various types of prior knowledge about the deflection spectrum. Our results show the capability and advantages of using a CS based approach for deflectometric imaging.Further, we present a method to characterize deflection spectra that captures its essence in a few parameters. We demonstrate that these parameters can be extracted directly from a few compressive measurements, without needing any costly reconstruction procedures, thereby saving a lot of computations. Then, a connection between the evolution of these parameters as a function of spatial locations and the optical characteristics of the objects under study is made. The experimental results with simple plano-convex lenses and multifocal intra-ocular lenses show how a quick characterization of the objects can be obtained using CS.

Complementary compressive imaging for the telescopic system by Wen-Kai Yu, Xue-Feng Liu, Xu-Ri Yao, Chao Wang, Yun Zhai and Guang-Jie Zhai

Conventional single-pixel cameras recover images only from the data recorded in one arm of the digital micromirror device, with the light reflected to the other direction not to be collected. Actually, the sampling in these two reflection orientations is correlated with each other, in view of which we propose a sampling concept of complementary compressive imaging, for the first time to our knowledge. We use this method in a telescopic system and acquire images of a target at about 2.0 km range with 20 cm resolution, with the variance of the noise decreasing by half. The influence of the sampling rate and the integration time of photomultiplier tubes on the image quality is also investigated experimentally. It is evident that this technique has advantages of large field of view over a long distance, high-resolution, high imaging speed, high-quality imaging capabilities, and needs fewer measurements in total than any single-arm sampling, thus can be used to improve the performance of all compressive imaging schemes and opens up possibilities for new applications in the remote-sensing area.

I note from their conclusion:

In summary, our results represent the first complementary compressive imaging of a target at about 2.0 km range with 20 cm resolution, realizing large FOV imaging over a long distance.

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