Conventional and digital holographies are proving to be increasingly important for studies of marine zooplankton and other underwater biological applications. This paper reports on the use of a subsea digital holographic camera (eHoloCam) for the analysis and identification of marine organisms and other subsea particles. Unlike recording on a photographic film, a digital hologram (e-hologram) is recorded on an electronic sensor and reconstructed numerically in a computer by simulating the propagation of the optical field in space. By comparison with other imaging techniques, an e-hologram has several advantages such as three-dimensional spatial reconstruction, non-intrusive and nondestructive interrogation of the recording sampling volume and the ability to record holographic videos. The basis of much work in optics lies in Maxwell's electromagnetic theory and holography is no exception: we report here on two of the numerical reconstruction algorithms we have used to reconstruct holograms obtained using eHoloCam and how their starting point lies in Maxwell's equations. Derivation of the angular spectrum algorithm for plane waves is provided as an exact method for the in-line numerical reconstruction of digital holograms. The Fresnel numerical reconstruction algorithm is derived from the angular spectrum method. In-line holograms are numerically processed before and after reconstruction to remove periodic noise from captured images and to increase image contrast. The ability of the Fresnel integration reconstruction algorithm to extend the reconstructed volume beyond the recording sensor dimensions is also shown with a 50% extension of the reconstruction area. Finally, we present some images obtained from recent deployments of eHoloCam in the North Sea and Faeroes Channel.

A noncontact method to identify sparsely distributed plastic pellets is proposed by integrating holography and Raman spectroscopy in this study. Polystyrene and poly(methyl methacrylate) resin pellets with a size of 3 mm located in a 20 cm water channel were illuminated using a collimated continuous wave laser beam with a diameter of 4 mm and wavelength of 785 nm. The same laser beam was used to take a holographic image and Raman spectrum of a pellet to identify the shape, size, and composition of material. Using the compact system, the morphological and chemical analysis of pellets in a large volume of water was performed. The reported method demonstrates the potential for noncontact continuous in situ monitoring of microplastics in water without collection and separation.

A digital holographic camera (eHoloCam) has been developed by us for in situ underwater studies of the distribution and dynamics of plankton and other marine organisms and particles. The eHoloCam uses a frequency-doubled Nd-YAG pulsed laser to freeze-frame rapidly moving particles and a CMOS imaging sensor for high-resolution image capture. Digital holograms are recorded at rates from 5 Hz to 25 Hz as holographic videos over a period of several hours. Data is stored in the camera on an embedded computer. eHoloCam is capable of recording all organisms and particles located in a water volume of 36.8 cm3 in a single hologram frame. The recorded holographic videos may subsequently be recreated numerically, using a variety of reconstruction algorithms, at a desired image plane.The vast amounts of data stored in holographic videos presents a major challenge for the automation of image extraction, identification of species and hence analysis of the holograms. In this paper, we describe some of the algorithms we use to optimise hologram reconstruction and, subsequently, image quality. We discuss the problems of automating the data extraction, the implementation of auto-focus methods and the definition of regions of interest in the eholovideo reconstruction procedures. In covering each of these and their amalgamation into a single algorithm, we will describe a complete image auto-extraction algorithm capable of scanning eholovideos and generating a directory of extracted, focussed bitmap-images. We go on to discuss possible analysis techniques that could be applied to resulting images in order to aid the extraction of particle information such as particles-per-volume and particle size ranges, and finally discuss the future implementation of particle autorecognition to perform species-specific analysis of eholovideos.

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We present a least-squares solution for the inverse problem in in-line digital holography which is based on a point source model. We demonstrate that by reformulating the reconstruction problem as an inverse problem and by integrating a contour gradient based auto-focus search algorithm into the reconstruction routine, a more fundamental solution for the inversion of a hologram can be attained. With this approach the inversion can be calculated without any prior knowledge of the object’s shape/size and without imposing any constraints on the imaging system. In a proof-of-concept study we show that our method facilitates a more accurate reconstruction, as compared to conventional methods, and that it facilitates object localization with an accuracy on the order of the optical wavelength.