This tool performs a majority (or modal) filter on a raster image. A mode filter assigns each cell in the output grid the most commonly occuring value, i.e. mode, in a moving window centred on each grid cell. Mode filters should only be applied to input images of a categorical data scale.Because it requires sorting the values in the window, a computationally intensive task, the mode filter is considerably less efficient than other smoothing filters. This may pose a problem for large images or large neighbourhoods.
Neighbourhood size, or filter size, is determined by the user-defined x and y dimensions. These dimensions should be odd, positive integer values (e.g. 3, 5, 7, 9, etc.) The user may also define the neighbourhood shape as either squared or rounded. A rounded neighbourhood approximates an ellipse; a rounded neighbourhood with equal x and y dimensions approximates a circle.
NoData values in the input image are ignored during filtering. When the neighbourhood around a grid cell extends beyond the edge of the grid, NoData values are assigned to these sites. The output raster is of the float data type and continuous data scale.
The following is an example of a Python script that uses this tool:
wd = pluginHost.getWorkingDirectory()
inputFile = wd + "input.dep"
outputFile = wd + "output.dep"
xDim = "3"
yDim = "3"
rounded = "false"
reflectEdges = "true"
args = [inputFile, outputFile, xDim, yDim, rounded, reflectEdges]
pluginHost.runPlugin("FilterMajority", args, False)
This is a Groovy script also using the tool:
def wd = pluginHost.getWorkingDirectory()
def inputFile = wd + "input.dep"
def outputFile = wd + "output.dep"
def xDim = "7"
def yDim = "7"
def rounded = "true"
def reflectEdges = "true"
String[] args = [inputFile, outputFile, xDim, yDim, rounded, reflectEdges]
pluginHost.runPlugin("FilterMajority", args, false)