In-line particle holography is subject to image deterioration due to intrinsic speckle noise. The resulting reduction in the signal to noise ratio (SNR) of the replayed image can become critical for applications such as holographic particle velocimetry (HPV) and 3D visualisation of marine plankton. Work has been done to extend the mono-disperse model relevant to HPV to include poly-disperse particle fields appropriate for the visualisation of marine plankton. Continuous and discrete particle fields are both considered. It is found that random walk statistics still apply for the poly-disperse case. The speckle field is simply the summation of the individual speckle patterns due to each scatter size. Therefore the characteristic speckle parameter (which encompasses particle diameter, concentration and sample depth) is also just the summation of the individual spedde parameters. This reduces the SNR calculation to the same form as for the mono-disperse case. For the continuous situation three distributions, power, exponential and Gaussian are discussed with the resulting SNR calculated. The work presented here was performed as part of the Holomar project to produce a working underwater holographic camera for recording plankton
