NNES global thresholding. (a) The conceptual decomposition of a confocal fluorescence image of the cytoskeleton. An Arabidopsis leaf confocal microscopic image of actin, as an example of the eukaryotic cytoskeleton, comprises of three components: ground noise, the mechanical noise of the sensor regardless of the true fluorescence signal, diffraction light, the unavoidable diffraction signal of fluorescence component around, and true actin signal. They correspond to the noise filtered by coarse background, noise additionally filtered by ILEE, and segmented actin components in the algorithm. (b) The scheme and demonstration of NNES. The curve reflects the NNE (negative non-connected component) count when certain global thresholding is applied to the raw images of 30 randomly selected samples. Their extremely smooth shape makes it easy to detect the peak as a feature value as the input for the coarse background estimation model. (i–iv) The demonstration of the filtered background at positions (i), (ii), (iii), and (iv) are shown above, where (iii) is adopted. The black area surrounded by colored area is the foreground information to be further processed. Scale bars are marked as red/yellow solid line.