Correcting saturation of detectors for particle/droplet imaging methods

Laser-based diagnostic methods are being applied to more and more flows of theoretical and practical interest and are revealing interesting new flow features. Imaging particles or droplets in nephelometry and laser sheet dropsizing methods requires a trade-off of maximized signal-to-noise ratio without over-saturating the detector. Droplet and particle imaging results in lognormal distribution of pixel intensities. It is possible to fit a derived lognormal distribution to the histogram of measured pixel intensities. If pixel intensities are clipped at a saturated value, it is possible to estimate a presumed probability density function (pdf) shape without the effects of saturation from the lognormal fit to the unsaturated histogram. Information about presumed shapes of the pixel intensity pdf is used to generate corrections that can be applied to data to account for saturation. The effects of even slight saturation are shown to be a significant source of error on the derived average. The influence of saturation on the derived root mean square (rms) is even more pronounced. It is found that errors on the determined average exceed 5% when the number of saturated samples exceeds 3% of the total. Errors on the rms are 20% for a similar saturation level. This study also attempts to delineate limits, within which the detector saturation can be accurately corrected. It is demonstrated that a simple method for reshaping the clipped part of the pixel intensity histogram makes accurate corrections to account for saturated pixels. These outcomes can be used to correct a saturated signal, quantify the effect of saturation on a derived average and offer a method to correct the derived average in the case of slight to moderate saturation of pixels.Peter A. M. Kal