Using disparity in digital holograms for three-dimensional object segmentation

Digital holography allows one to sense and reconstruct the amplitude and phase of a wavefront reflected from or transmitted through a real-world three-dimensional (3D) object. However, some combinations of hologram capture setup and 3D object pose problems for the reliable reconstruction of quantitative phase information. In particular, these are cases where the twin image or noise corrupts the reconstructed phase. In such cases it is usual that only amplitude is reconstructed and used as the basis for metrology. A focus criterion is often applied to this reconstructed amplitude to extract depth information from the sensed 3D scene. In this paper we present an alternative technique based on applying conventional stereo computer vision algorithms to amplitude reconstructions. In the technique, two perspectives are reconstructed from a single hologram, and the stereo disparity between the pair is used to infer depth information for different regions in the field of view. Such an approach has inherent simplifications in digital holography as the epipolar geometry is known a priori. We show the effectiveness of the technique using digital holograms of real-world 3D objects. We discuss extensions to multi-view algorithms, the effect of speckle, and sensitivity to the depth of field of reconstructions.