This tool performs a standard deviation filter on a raster image, i.e. it calculates the standard deviation within a neighbouring area around each grid cell. A standard deviation filter can be used to emphasize the local variability in an image. This can be useful for edge detection.
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("FilterStandardDeviation", 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("FilterStandardDeviation", args, false)