Abstract

Optical sensing and imaging applications often suffer from a combination of low resolution object reconstructions and a large number of sensors which, depending on frequency, can be quite expensive or bulky. It is therefore desirable to minimize the number of sensors (which reduces cost) for a given target resolution level (image quality) and permissible total sensor array size (compactness). Equivalently, for a given imaging hardware one seeks to maximize image quality, which in turn means fully exploiting the available sensors as well as all priors about the properties of the sought-after objects such as sparsity properties, and other, which can be incorporated into reconstruction schemes. This paper proposes a compressive-sensing-based method to process through-focus optical field data captured at a sensor array. The proposed approach treats in-focus and out-offocus data as projective measurements for compressive sensing, and assumes that the objects are sparse under known transformations applied to them. The proposed compressive through-focus imaging is illustrated for both coherent and incoherent light. The results illustrate the combined use of through-focus imaging and compressive sensing techniques, and provide insight on the information in in-focus and out-of-focus data for coherent as well as incoherent light.

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