We address the use of transmission geometry volume holograms as depth-selective imaging elements in profilometry. We derive the point-spread function (PSF) of the volume holographic imaging system using volume diffraction theory and use the PSF to estimate depth resolution. Experimentally measured PSF and depth-selective images are presented to verify the theoretical predictions. Furthermore, we show that with prior knowledge of the object, depth resolution can be improved greatly with the method of inclined illumination. In more general cases, super resolution can also be achieved with digital post-processing methods such as Viterbi algorithm (VA). We show that computational complexity can be reduced with surface constraints. Resolution improvement by a factor of 5 was obtained in experimental demonstration.
We present an overview of imaging systems that incorporate a volume hologram as one of the optical field processing elements in the system. We refer to these systems as volume holographic imaging (VHI) systems. The volume hologram is recorded just once, and the recording parameters depend on the functional requirements of the imaging system. The recording step offers great flexibility in designing application-specific imaging systems. We discuss how a VHI system can be configured for diverse imaging applications ranging from surface profilometry to real-time hyperspectral microscopy, and summarize recent developments in this field.
Volume holographic imaging (VHI) utilizes the Bragg selectivity of volume holograms to achieve 3D optical slicing. The depth resolution of VHI degrades quadratically with increasing object distance like most 3D imaging systems. We have devised an imaging scheme that takes advantage of the superior lateral resolution of VHI and a-priori surface information about the object to build a profilometer that can resolve 50 μm features at a working distance of ≈ 50 cm. We discuss the scheme and present experimental results of surface profiles of MEMS devices.
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