## Imaging Systems Laboratory: Research on Digital Holography## ObjectiveWe develop computational algorithms — mostly inverse imaging — for sectional image reconstruction and resolution enhancement in digital holography. ## IntroductionDigital holography is about the acquisition of holographic image data
using a digital sensor, and the subsequent processing to reconstruct
individual images. One important use is in three-dimensional microscopy.
In fact, holography was first invented for microscopy, and making the
recording digital has the benefit of enormous processing power in the
recovery of images at specific sections, a process commonly called
We have worked primarily with a specific form of digital holography called
Fig 1: The optical scanning holography system. [1] Using and to denote the transverse spatial frequency coordinates, we can derive the optical transfer function (OTF) to be where is the wave number. The free-space spatial impulse response is then For an object with complex amplitude , the complex hologram is given by The goal of sectioning is to recover from at specific depths (i.e. different values of ). ## Inverse imagingThe conventional method for optical sectioning suffers primarily from
is from the observed hologram, and is known if we know where the sections are. We can therefore derive from various inverse imaging techniques. Our first method, using (the simplest) Tikhonov regularization, is reported in [2].
An improvement, which using total variation regularization to preserve the edges better, is reported in [3].
## Examples## (1) Biological sample (fluorescent beads)We experimentally capture a hologram of fluorescent beads (DukeR0200,
2m in diameter, excitation around 542 nm, emission around 612 nm).
The beads mainly assemble at the top and bottom surfaces. We then reconstruct
the two sections. These are shown in Figure 2. In the reconstructed sections
we can clearly see the individual beads. Fig 2: [left] Volume view; [right] Two sections reconstructed by the inverse imaging method [1]. ## (2) Blind sectional image reconstructionWe derive a technique that can estimate where the sections of interest are in the hologram. Such information is then used in the inverse imaging algorithm. Details of our edge-based blind section identification technique can be found in [4]. A representative example is given in Figure 3. Fig 3: [left] Two reconstructed sectional images by the convolution method; [right] by the inverse imaging method. [4] ## (3) Multiple sectional image reconstructionOne advantage of the inverse imaging method is that it can be applied on objects with multiple sections. An example with five sections is given in Figure 4. Here, the locations of the five sections are first estimated by the blind reconstruction technique [4] before using the information in the inverse imaging algorithm. Fig 4: [top] Locations of the five sections; [bottom] Sectional image reconstruction. [4] ## Selected referencesEdmund Y. Lam, Xin Zhang, Huy Vo, Ting-Chung Poon, and Guy Indebetouw, “Three-dimensional microscopy and sectional image reconstruction using optical scanning holography,” *Applied Optics*, Vol. 48, no. 34, pp. H105–H112, December 2009. (pdf copy) (bibtex entry)
Xin Zhang, Edmund Y. Lam, and Ting-Chung Poon, “Reconstruction of sectional images in holography using inverse imaging,” *Optics Express*, vol. 16, no. 22, pp. 17215–17226, October 2008. Also published in*The Virtual Journal for Biomedical Optics*, vol. 3, no. 12, December 2008. (pdf copy) (bibtex entry)
Xin Zhang and Edmund Y. Lam, “Edge-preserving sectional image reconstruction in optical scanning holography,” *Journal of the Optical Society of America A*, vol. 27, no. 7, pp. 1630–1637, July 2010. Also published in*The Virtual Journal for Biomedical Optics*, vol. 5, no. 11, August 2010. (pdf copy) (bibtex entry)
Xin Zhang, Edmund Y. Lam, Taegeun Kim, You Seok Kim and Ting-Chung Poon, “Blind sectional image reconstruction for optical scanning holography,” *Optics Letters*, Vol. 34, no. 20, pp. 3098–3100, October 2009. (pdf copy) (bibtex entry)
## Current members## External Collaborators and former members |