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.