Abstract
Holography provides a means for indirect acquirement and reconstruction of 3-D object features. Here, we demonstrate high-resolution viewpoint object inference by formulating the object's reconstruction in the framework of compressive sensing. Further, when the object is dominated by speckle noise and cannot be considered to be sparse, we propose a digital resampling diversity compressive sensing approach to reconstruct a high-quality viewpoint inferred object. The results can be used in all types of holography for display and research purposes.
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