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Illumination correction is often important for both accurate segmentation and for intensity measurements. This example shows how the CorrectIlluminationCalculate and CorrectIlluminationApply modules are used to compensate for the non-uniformities in illumination often present in microscopy images.

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This is a simple example of a DNA damage assay using single cell gel electrophoresis. Here, the measurement of interest is the length and intensity of the comet tail. Also, illumination correction is used to reduce background fluorescence prior to measurement. Also shown is a silver-stained comet example in which the percentage of DNA contained in the tail is calculated.

Example Images: Packaged together with the cellprofiler pipeline file. 

Simple spatial filters can be used to suppress noise in raw image data (i.e. by averaging intensities). The best choice of filter depends on the nature of the noise, but Gaussian filtering works well for Poisson noise (i.e. commonly observed photon-counting shot noise); whereas a median filter is ideal for salt-and-pepper noise. A larger filter radius leads to stronger noise suppression but more blurring. The URL above describes the simple 2D spatial filters available in ImageJ, but similar filters are available in most software. For 3D data, 3D versions of these filters work best (since there are more pixels to average within the same radius).