De-noising of SIMS images via wavelet shrinkage

Two-dimensional element distributions generated by scanning secondary ion mass spectrometry (SIMS) are characterised by Poisson statistics of small integer values, specially when the concentration of the measured element is in the sub-ppm range. To achieve high signal-to-noise ratios extremely long measurement time is needed. Because of the signal fluctuations from one measurement point to the next, structures even larger than the resolution of the instrument may not be detectable if the differences in concentration are small. This paper reports the application of a wavelet shrinkage algorithm for de-noising of images following Poisson distribution. In reconstructions of SIMS images resulting from this algorithm the noise is significantly suppressed without great loss of lateral resolution.