We propose a full-color holographic three-dimensional imaging system that composes a recording stage, a transmission and processing stage and reconstruction stage. In recording stage, color optical scanning holography (OSH) records the complex RGB holograms of an object. In transmission and processing stage, the recorded complex RGB holograms are transmitted to the reconstruction stage after conversion to off-axis RGB holograms. In reconstruction stage, the off-axis RGB holograms are reconstructed optically.
We demonstrate a 3D holographic imaging system that composed 1. Recording stage, 2. Processing and transmission stage and 3 Reconstruction stage. First, we record the hologram of a diffusely reflective object using optical scanning holography without speckle noise as well as twin image and background noises. Second, we convert the hologram into an off-axis horizontal-parallax-only (HPO) hologram. Third, we reconstruct the off-axis HPO hologram using amplitudeonly SLM. To the best of our knowledge, this is the first demonstration that records and displays an HPO hologram of a diffusely reflective object optically.
The optical imaging takes advantage of coherent optics and has promoted the development of visualization of biological
application. Based on the temporal coherence, optical coherence tomography can deliver three-dimensional optical
images with superior resolutions, but the axial and lateral scanning is a time-consuming process. Optical scanning
holography (OSH) is a spatial coherence technique which integrates three-dimensional object into a two-dimensional
hologram through a two-dimensional optical scanning raster. The advantages of high lateral resolution and fast image
acquisition offer it a great potential application in three-dimensional optical imaging, but the prerequisite is the accurate
and practical reconstruction algorithm. Conventional method was first adopted to reconstruct sectional images and
obtained fine results, but some drawbacks restricted its practicality. An optimization method based on 2 l norm obtained
more accurate results than that of the conventional methods, but the intrinsic smooth of 2 l norm blurs the reconstruction
results. In this paper, a hard-threshold based sparse inverse imaging algorithm is proposed to improve the sectional image
reconstruction. The proposed method is characterized by hard-threshold based iterating with shrinkage threshold strategy,
which only involves lightweight vector operations and matrix-vector multiplication. The performance of the proposed
method has been validated by real experiment, which demonstrated great improvement on reconstruction accuracy at
appropriate computational cost.