Underwater optical imaging advances from 2005 to the present are reviewed. Research and technical innovations are synopsized and organized much as the previous report (Kocak and Caimi, 2005) was. Examples of several recent novel system applications are given, as are brief summaries of emerging underwater imaging research and development trends.

A Focus on Recent Developments and Trends in Underwater Imaging

An investigation is reported of the identification and measurement of region of interest (ROI) in quantitative phase-contrast maps of biological cells by digital holographic microscopy. In particular, two different methods have been developed for in vitro bull sperm head morphometry analysis. We show that semen analysis can be accomplished by means of the proposed techniques . Extraction and measurement of various parameters are performed. It is demonstrated that both proposed methods are efficient to skim the data set in a preselective analysis for discarding anomalous data.

Identification of bovine sperm head for morphometry analysis in quantitative phase-contrast holographic microscopy

The paper presents a technique of manipulating the pupil function in the optical scanning holography (OSH) system to detect the edge of a three-dimensional object. OSH is a fast biomedical imaging system that scans a three-dimensional (3D) object and encodes its intensity information into a two-dimensional hologram. The reconstruction of sectional images from a hologram has been well discussed as post-processing methods. However, manipulating pupil functions as a pre-processing technique has been less investigated. The latter can detect any specific part of an object by manipulating the pupil function. Here, we focus on the edge detection of a 3D object, which is implemented by configuring two pupil functions as a Dirac delta function and the Laplacian of the Gaussian, respectively. The simulated experiment demonstrates that the technique is a real-time pre-processing method to obtain the edge of the 3D object.

Edge detection of three-dimensional objects by manipulating pupil functions in an optical scanning holography system

An experimental method to visualize a 3D-region of interest (ROI) by means of an astigmatic Gaussian beam is proposed. This method allows to reduce the amount of image planes to be reconstructed thus saving computational time. ROI determination is performed without any computational step: particles that are located in the ROI can be distinguished from the others according to the hyperbolic shape of their diffraction pattern. Theoretical location of the ROI is determined by using the ABCD approach proposed in a previous paper [Appl. Opt. 47, 4147]. Experimental results are presented.

https://www.jeos.org/index.php/jeos_rp/article/download/09038/452

Determination of 3D-region of interest using digital in-line holography with astigmatic Gaussian beams

Phytoplankton, as an important component of marine ecosystem, play a key role in understanding marine resources and monitoring marine environment. In this paper, under the suggestion of marine biology professional researcher, we selected six kinds of phytoplankton commonly found in China’s coastal areas and conducted digital holographic microscopic imaging experiments to obtain their holograms. Then, the angular spectrum reconstruction algorithm was used to conduct diffraction reconstruction of the phytoplankton hologram to achieve clear imaging of the algae target. A threshold based image segmentation algorithm is used to segment the phytoplankton target area and obtain image dataset. Finally, transfer learning is used to train on the pre-trained model. Experimental results show that the classification accuracy of the trained network on the test set can reach 95.7%.

Classification of phytoplankton digital holograms using transfer learning

Selective reconstruction withdatareduction isthe keytoefficient dataanalysis andhighquality imagereconstruc- tions fromdigital holograms. Thispaperpresents anefficient methodofextracting 3D regions ofinterest (ROTs) ofobject volumedirectly froma hologram. Thenewmethodconsists ofa rapidfocusdetection algorithm, a summation kernel for computing asumimageontowhichofasequence ofobject images areprojected andanimagesegmentation algorithm. Thefocus detection algorithm isbasedonthe11normoftheobject spectral components andworksdirectly onthehologram. Itestimates thedepthdistances atwhichobjects canbefoundin-focus. The summation kernel isthenemployed toobtain sumimages thatare effectively theparallel projection ofobject images located within eachdetected rangeoffocusing distances. Thelateral support of theseROTsarethenobtained bysegmenting these sumimages. Thewholeprocess doesnotrequire full reconstruction ofthe object images throughout the3Dvolume. Basedonalens-less DHI camerasystem jointly developed atMIT andWHOI,the new3DROIextraction technique hasbeenapplied toplankton holograms obtained inthelaboratory andonshipboard. Results fromplankton holograms aredemonstrated.

Weichang Li

Papers

Rapid extraction of 3D regionsof interest from digital holograms