Partially coherent digital in-line holographic microscopy in characterization of a microscopic target

Abstract

Digital holographic microscopy enables the capture of large three-dimensional volumes. Instead of using a laser as an illumination source, partially coherent alternatives can be used, such as light-emitting diodes, which produce parasitic reflection and speckle-free holograms. Captured high-contrast holograms are suitable for the characterization of micrometer-sized particles. As the reconstructed phase is not usable in the case of multiple overlapping objects, depth extraction can be conducted on a reconstructed intensity. This work introduces a novel depth extraction algorithm that takes into consideration the possible locations of multiple objects at various depths in the imaged volume. The focus metric, the Tamura coefficient, is applied for each pixel in the reconstructed amplitude throughout the volume. This work also introduces an optimized version of the algorithm, which is run in two stages. During the first stage, coarse positions of the objects are extracted by applying the Tamura coefficient to nonoverlapping window blocks of intensity reconstructions. The second stage produces high-precision characterizations of the objects by calculating the Tamura coefficient with overlapping window blocks around axial positions extracted in the first stage. Experimental results with real-world microscopic objects show the effectiveness of the proposed method.

Digital Holographic Microscopy in Remote Potable Water Monitoring

“…3. The 3D locations of all of the particles in the field of view can be obtained through automated means [10,11].…”

Space-variant video compression and processing in digital holographic microscopy sensor networks with application to potable water monitoring

“…The major disadvantages of each approach could be avoided, without sacrificing either one's advantages. The challenge is to find algorithms for the measurement nodes that are: 1. effective: measurement node algorithms must be effective at preprocessing and compressing the hologram video data such that network bandwidth requirements are low (compared to transmitting the raw video data) and water temporal sampling density is high, and 2. efficient: at the same time, the measurement node algorithms need to be computationally simple and efficient such that the computer has sufficiently modest computing hardware [38] is calculated for each pixel on each layer of the inverted amplitude reconstruction volume by using blockwise processing [37]. Variance and amplitude are calculated in the same manner.…”

“…The rayon fibers were captured with the setup described in Ref. [37] and the other two as described in Section 4 of this paper. Tamura contrast and variance work well for E. coli and latex beads; however, variance identifies only the edges of the rayon fibers.…”

“…As the system is required to be near-real-time, algorithms need to be optimized and chosen on the basis of the specific application. In the literature, objects have been found in hologram reconstruction volumes using amplitude analysis [27], edge detection [36], and contrast analysis [37]. However, as shown in Fig.…”

“…In order to image process and analyze these holograms, an automated procedure was developed. The objects were localized and segmented using Tamura coefficient approximation [37]. The 3D blobs (regions) were classified according to their morphology by calculating their eccentricity [29], as…”