segmentation | R Documentation |
This function uses the open-source software of GRASS and SAGA GIS
to fulfill an imagery segmentation. It is possible to decide bet
ween SAGA and GRASS GIS segmentation.
In SAGA GIS, the tools SEED GENERATION or FAST REPRESENTATIVENESS
are used for computing seed points. Then, the SEEDED REGION GROWING al-
gorithm is used for the segmentation.
In GRASS GIS, the tool OBJECT-SEGMENTATION (i.segment) is used
for the segmentation. There is also the possibility to use
the new SLIC algorithm.
Moreover, there is the option to compute a generalisation of
segments by (multiple) majority filter (SAGA GIS) at the end.
segmentation(Tool, Segments.Grid, Segments.Poly, Input.Grid, Saga.Output.Grid = file.path(tempdir(), paste0("SagaRepresentativenessOutputGrid", par.i, ".sgrd")), Saga.Output.Lod = file.path(tempdir(), paste0("SagaRepresentativenessOutputLod", par.i, ".sgrd")), Output.Seeds = file.path(tempdir(), paste0("OutputSeed", par.i, ".sgrd")), Fast.Representativeness.LevelOfGeneralisation = "10.0", Saga.Similarity = file.path(tempdir(), paste0("SagaSimilarity", par.i, ".sgrd")), Saga.Segments.Seeds.Table = file.path(tempdir(), paste0("SagaSegmentsSeedsTable", par.i, ".mtab")), Saga.Segmentation.Normalize = "0", Saga.Segmentation.Neighbourhood = "0", Saga.Segmentation.Method = "0", Saga.Segmentation.Sig.1 = "1.0", Saga.Segmentation.Sig.2 = "1.0", Saga.Segmentation.Threshold = "0.0", Saga.Segmentation.Refresh = "0", Saga.Segmentation.Leafsize = 256, Split = "0", Grass.Segmentation.Threshold = NULL, Grass.Segmentation.Weighted = FALSE, Grass.Segmentation.Method = "region_growing", Grass.Segmentation.Similarity = "euclidean", Grass.Segmentation.Minsize = 15, Grass.Segmentation.Memory = 300, Grass.Segmentation.Iterations = 50, Grass.Segmentation.Seeds = NULL, Grass.Segmentation.Neighbourhood = "0", Segmentation.Boundary.Grid = NULL, Grass.Segmentation.Goodness = paste0("Grass.Segmentation.Goodness", par.i), AllVertices = "FALSE", NoData = FALSE, Mask = NULL, NoData.Flag = -99999, show.output.on.console = FALSE, Seed.Method = "", Seed.Generation.Variance = paste0(tempdir(), paste0("SeedGenerationVariance", par.i, ".sgrd")), Seed.Generation.Points = file.path(tempdir(), paste0("SeedGenerationPoints", par.i, ".shp")), Seed.Generation.Type = "0", Seed.Generation.Scale = "10.0", Generalisation.Flac = FALSE, Generalization.Mode = "1", Generalization.Radius = "1", Generalization.Threshold = "0.0", env = RSAGA::rsaga.env(), Grass.SLIC.Iter = 10, Grass.SLIC.Superpixels = 200, Grass.SLIC.Step = 0, Grass.SLIC.Compactness = 1, Grass.SLIC.Superpixels.MinSize = 1, Grass.SLIC.Memory = 300, Grass.SLIC.Perturb = 0, burn.Boundary.into.Segments = FALSE, estimateScaleParameter = FALSE, Mode.Filter.Flac = FALSE, Mode.Filter.Size = 7, Mode.Filter.Segment.MinSize = 3, par.i = "", Sieving.Flac = FALSE, Sieving.Mode = "0", Sieving.Thresh = 4, Sieving.Expand = 4, ...)
Tool |
GRASS, SAGA or GRASS Superixels SLIC. Definition of open-source software which will be used |
Segments.Grid |
output path of raster with segments |
Segments.Poly |
output path of polygon with segments |
Input.Grid |
vector containing grid(s) for segmentation. It is possible to add multiple gridsm, as well as different grids even in combination of SAGA and GRASS. By using SAGA and GRASS combination the following separation must be used: '<>' (SAGA before GRASS grids!) |
Saga.Output.Grid |
output of FAST REPRESENTATIVENESS in SAGA. Default: temp |
Saga.Output.Lod |
output Lod of Representativeness Function in SAGA. Default: temp |
Output.Seeds |
output of seed points as raster, used for segmentation. Default: temp |
Fast.Representativeness.LevelOfGeneralisation |
determining number of seed points. Default: "10.0" |
Saga.Similarity |
output of similarity grid. Default: temp |
Saga.Segments.Seeds.Table |
table of seeds information. Default: temp |
Saga.Segmentation.Normalize |
normalisation during imagery segmentation. Default: "0" |
Saga.Segmentation.Neighbourhood |
neighbourhood considered during imagery segmentation. Default: "0" (4, alternative: "1" for 8) |
Saga.Segmentation.Method |
segmentation method during imagery segmentation. Default: "0" (feature space and position) |
Saga.Segmentation.Sig.1 |
variance in feature space in imagery segmentation. Default: "1.0" |
Saga.Segmentation.Sig.2 |
variance in position space in imagery segmentation. Default: "1.0" |
Saga.Segmentation.Threshold |
similarity threshold for joining pixel to segments in imagery segmentation. Default: "0.0" |
Saga.Segmentation.Refresh |
refresh image after imagery segmentation. Default: "0" |
Saga.Segmentation.Leafsize |
parameter for speed optimation in imagery segmentation. Default: 256 |
Split |
split polygons to singlepart in vectorising grid classes. Default: "0" |
Grass.Segmentation.Threshold |
similarity threshold for joining pixel to segments. Default: NULL, 0.0 is not allowed |
Grass.Segmentation.Weighted |
option of weighing input grids in segmentation. Default: "FALSE" |
Grass.Segmentation.Method |
type of GRASS Segmentation. Default: "region_growing" |
Grass.Segmentation.Similarity |
distance measurement of similarity. Default: "euclidean" |
Grass.Segmentation.Minsize |
minsize of segment. Default: 15 |
Grass.Segmentation.Memory |
memory to be used for segmentation. Default: 300 |
Grass.Segmentation.Iterations |
amount of allowed iterations. Default: 50 |
Grass.Segmentation.Seeds |
input of seeds raster. Enables bottom-up segmentation. Default: NULL |
Segmentation.Boundary.Grid |
input of boundary raster. Enables top-down (or hierarchical) segmentation. Default: NULL. NULL values must be 0 (or any other not segment value!). |
Grass.Segmentation.Goodness |
name for output goodness of fit estimate map. Default:"Grass.Segmentation.Goodness" |
AllVertices |
use all vertices by vectorising grid classes. Default: "FALSE" |
NoData |
input data contains NoData value. Default: FALSE |
Mask |
mask raster to mask NoData from input. Default: NULL |
show.output.on.console |
show output on console. Default: FALSE |
Seed.Method |
type of seed method for getting seeds. Default: "" (alternative: "Fast Representativeness", "Seed Generation", "Superpixels SLIC") |
Seed.Generation.Variance |
output raster with variance of seed generation. Default: temp |
Seed.Generation.Points |
output of seed points as shapefile. Default: temp |
Seed.Generation.Type |
option of seed generation type. Default:"0" (minima of variance, alternative: maxima of variance) |
Seed.Generation.Scale |
determining number of seed points in seed generation. Default: "10.0" |
Generalisation.Flac |
performing (multiple) majority filter on segments. Default: FALSE |
Generalization.Mode |
search mode by filtering: Default: "1" (circle, alternative: square) |
Generalization.Threshold |
threshold for applying majority filters. Default: "0.0" |
env |
environment of RSAGA. Default: RSAGA::rsaga.env() |
Grass.SLIC.Iter |
maximum number of iterations. Default: 10 |
Grass.SLIC.Superpixels |
approximate number of output super pixels. Default: 200 |
Grass.SLIC.Step |
distance (number of cells) between initial super pixel centers. A step size > 0 overrides the number of super pixels. Default: 0 |
Grass.SLIC.Compactness |
compactness. A larger value causes more compact superpixels. Default: 1.0 |
Grass.SLIC.Superpixels.MinSize |
minimum superpixel size. Default: 1 |
Grass.SLIC.Memory |
memory in MB. Default: 300 |
Grass.SLIC.Perturb |
Perturb initial super pixel centers. Percent of intitial superpixel radius. Default: 0, range: 0-100 |
burn.Boundary.into.Segments |
vector specifing if boundary grid is burned into segmentation (1) or seeds (2). Default: FALSE, maximum length: 2 |
estimateScaleParameter |
must be only be TRUE when scale parameter function is used. Default: FALSE |
Mode.Filter.Flac |
re-assign objects of a specific size based on mode values to its surroundings (moving window). Default: FALSE |
Mode.Filter.Size |
moving window size of mode-filter. Default: 3 |
Mode.Filter.Segment.MinSize |
objects smaller and equal to this size are selected for filtering. Default: 3 |
par.i |
run number. Default: "" |
Sieving.Flac |
perform sieving. Default: FALSE |
Sieving.Mode |
sieving mode. Default:"0" |
Sieving.Thresh |
minsize of clumps. Default: 4 |
Sieving.Expand |
expand cells using majority filter. radius in cell sizes. Default:4 |
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