Syntax

   FACTORY_DEF <ReaderKeyword> RasterConvolverFactory
   [FACTORY_NAME <factory name>]
   [INPUT FEATURE_TYPE <factory type>
      [<attribute name> <attribute value>]*
      [<feature function>]*]*
   [CONVOLUTION_FILTER <convolution filter value>]
   [KERNEL_SIZE <kernel size value>]
   [KERNEL_WEIGHTS <kernel weights value>]
   [KERNEL_DIVISOR (<kernel divisor value>|SumOfKernelWeights)]
   [KERNEL_OPERATION (Majority|Maximum|Mean|Median|Minimum|Minority|Range|StandardDeviation|Sum|Variety)]
   [EDGE_HANDLING (UseNoDataOutsideRaster|ExtendBorderValues)]
   [CENTER_PIXEL_NODATA_HANDLING (OutputNodata|IgnorePixelNodata)]
   [NEIGHBOR_PIXEL_NODATA_HANDLING (UseCenterPixel|IgnorePixelNodata)]
   [PRESERVE_BAND_INTERPRETATION (Yes|No)]
   [ZERO_WEIGHT_HANDLING (UseZeroWeightValues|IgnoreZeroWeightValues)]
   [OUTPUT OUTPUT FEATURE_TYPE <feature type>
      [<attribute name> <attribute value>]*
      [<feature function>]*]*

Overview

   This factory is used to apply various convolution filters to rasters. There is a list of
   pre-defined filters specified and users are able to specify custom filters.

   Convolution is the process of adding each element of the image to its local neighbors, weighted
   by the kernel. Therefore, one of the most common operations is addition.

Parameters

   CONVOLUTION_FILTER

      List of predefined convolution filters and an option to specify a custom filter by specifying
      'User Defined'

   KERNEL_SIZE

      Must be odd and greater or equal to 3

   KERNEL_WEIGHTS

      Must be a KERNEL_SIZE * KERNEL_SIZE matrix of floating point values. The kernel must be square,
      with an odd size and at least 3x3.

   KERNEL_DIVISOR

      After applying the filter to a given pixel, the resulting value is divided by the divisor.
      Can be any floating point value, except 0. Otherwise, if SumOfKernelWeights is specified
      the divisor will be equal to the sum of weighs in the kernel specified

   KERNEL_OPERATION

      For each pixel in the local neighborhood, weight the values using the kernel weights and
      calculate the output by applying one of the following to each weighted value:
      [Majority|Maximum|Mean|Median|Minimum|Minority|Range|StandardDeviation|Sum|Variety]

   EDGE_HANDLING

      When processing the edges of the raster, some parts of the kernel might be outside. This
      parameter specifies how to treat those values. The options are:
         UseNoDataOutsideRaster - values outside raster will be substituted with Nodata
         ExtendBorderValues - edges of the raster will be extended (cloned) beyond the edges of the
                              raster for the purposes of the calculation.

   CENTER_PIXEL_NODATA_HANDLING

      Determines what to do when the center pixel being processed is Nodata:
         OutputNodata - if the source center pixel is Nodata, the result value is also Nodata
         IgnorePixelNoData - if the center is Nodata, the center value will be weighted as 0,
                             essentially excluding it from the calculation of the final value

   NEIGHOR_PIXEL_NODATA_HANDLING

      For each pixel in neighborhood if the value is Nodata:
         UseCenterPixel - substitute Nodata with the value of the center pixel. The value of the
                          center pixel will be determined using CENTER_PIXEL_NODATA_HANDLING if the
                          center value was Nodata as well
         IgnorePixelNoData - weight that pixel as 0, essentially excluding it from the calculation

   PRESERVE_BAND_INTERPRETATION

      If the parameter is set to Yes, interpretation for each band will be preserved

   ZERO_WEIGHT_HANDLING

      Specifies how zero weight values in the kernel will be handled.
         UseZeroWeightValues - Values with zero weight will be included in calculations (e.g. when
                               calculating the Mean, a value with zero weight will still contribute
                               to the divisor).
         IgnoreZeroWeightValues - Values with zero weight will be ignored in calculations (e.g. when
                                  calculating the Mean, a value with zero weight will not contribute
                                  to the divisor).

Output Tags

   The RasterConvolverFactory supports the following output tags.

   OUTPUT

      Output raster after applying the convolution filter to each pixel

   REJECTED

      If there are any incorrect transformer parameters or the input is incorrect, the feature with
      that raster will be rejected