The Binary Thresholding function creates a raster output that divides your raster into two distinct classes. The algorithm behind the Binary Thresholding function, the Otsu method, was designed to distinguish between background and foreground in imagery by creating two classes with minimal intraclass variance (Otsu 1979). When working with a raster dataset that has a unimodal distribution, Binary Thresholding divides the data into two distinct classes. It creates a high-value class, displayed with white pixels, and a low-value class, displayed with black pixels.
The input for this function is Input Raster.
- Otsu, Nobuyuki. "A Threshold Selection Method from Gray-Level Histograms." IEEE Transactions on Systems, Man, And Cybernetics 9, no. 1 (1979): 62–66.