This tool performs a mean filter on a raster image. A mean filter can be used to emphasize the longer-range variability in an image, effectively acting to smooth the image. This can be useful for reducing the noise in an image. The algorithm operates by calculating the average value in a moving window centred on each grid cell. Although commonly applied in digital image processing, mean filters are generally considered to be quite harsh, with respect to their impact on the image, compared to other smoothing filters such as the edge-preserving smoothing filter (bilateral), median, Gaussian, or Olympic filters.
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... 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("FilterMean", 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("FilterMean", args, false)