Compressive Fresnel digital holography using Fresnelet based sparse representation

Compressive sensing (CS) in digital holography requires only very less number of pixel level detections in hologram plane for accurate image reconstruction and this is achieved by exploiting the sparsity of the object wave. When the input object fields are non-sparse in spatial domain, CS demands a suitable sparsification method like wavelet decomposition. The Fresnelet, a suitable wavelet basis for processing Fresnel digital holograms is an efficient sparsifier for the complex Fresnel field obtained by the Fresnel transform of the object field and minimizes the mutual coherence between sensing and sparsifying matrices involved in CS. The paper demonstrates the merits of Fresnelet based sparsification in compressive digital Fresnel holography over conventional method of sparsifying the input object field. The phase shifting digital Fresnel holography (PSDH) is used to retrieve the complex Fresnel field for the chosen problem. The results are presented from a numerical experiment to show the proof of the concept.