pktools 2.6.7
Processing Kernel for geospatial data
pksieve

program to sieve filter raster image

SYNOPSIS

Usage: pksieve -i input [-s size] -o output

Options: [-c 4|8] [-b band] [-m mask] [-ot type] [-of format] [-co option]* [-ct table]

Description

The utility pksieve filters small objects (maximum size defined with the option -s) in a raster by replacing them to the largest neighbor object. In this context, objects are defined as pixels of the same value that are also connected. The connection can be defined in four directions (N-S and W-E: set option -c 4) or eight directions (N-S, W-E and diagonals NW-SE, NE-SW: set option -c 8).

Options

  • use either -short or --long options (both --long=value and --long value are supported)
  • short option -h shows basic options only, long option --help shows all options
    short long type default description
    i input std::string Input image file
    s size int 0 raster polygons with sizes smaller than this will be merged into their largest neighbour. No sieve is performed if size = 0
    o output std::string Output image file
    c connect int 8 the connectedness: 4 directions or 8 directions
    b band int 0 the band to be used from input file
    m mask std::string Use the first band of the specified file as a validity mask (zero is invalid, non-zero is valid).
    ot otype std::string Data type for output image ({Byte/Int16/UInt16/UInt32/Int32/Float32/Float64/CInt16/CInt32/CFloat32/CFloat64}). Empty string: inherit type from input image
    co co std::string Creation option for output file. Multiple options can be specified.
    ct ct std::string color table (file with 5 columns: id R G B ALFA (0: transparent, 255: solid)

Usage: pksieve -i input [-s size] -o output

Examples

Some examples how to use pksieve can be found here