This study investigates segmentation algorithms applicable to digital holography. An assessment of image segmentation tecnhniques applied to intensity images of reconstructions of digital holograms is provided. Digital holography differs from conventional imaging as 3D information is encoded. This allows depth information to be exploited so that focusing of 3D objects, or part there of, at different depths can be achieved. In this paper, segmentation of features is attained in microscopic and macroscopic scenes. We investigate a number of recently proposed segmentation techniques including (i) depth from focus, (ii) active contours and (iii) hierarchical thresholding. The influence of noise reduction on the segmentation capabilities of each of the techniques on these scenes is demonstrated. For the macrocsopic scenes, each technique is applied before and after speckle noise reduction is performed using a wavelet based approach. The performance of the segmentation techniques on the intensity information obtained from reconstructed holograms of microscopic scenes is also investigated before and after twin-image reduction has been applied. A comparison of the techniques and their performances in these circumstances is provided.