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Image filtering

BoyutAzaltma (ica)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Algorithm [selection]

<put parameter description here>

Options:

  • 0 — ica

Default: 0

number of iterations [number]

<put parameter description here>

Default: 20

Give the increment weight of W in [0, 1] [number]

<put parameter description here>

Default: 1

Number of Components [number]

<put parameter description here>

Default: 0

Normalize [boolean]

<put parameter description here>

Default: True

Çıktılar

Output Image [raster]
<put output description here>
Inverse Output Image [raster]
<put output description here>
Transformation matrix output [file]
<put output description here>

Konsol kullanımı

processing.runalg('otb:dimensionalityreductionica', -in, -method, -method.ica.iter, -method.ica.mu, -nbcomp, -normalize, -out, -outinv, -outmatrix)

Ayrıca bakınız

Boyutİndirgeme (maf)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Algorithm [selection]

<put parameter description here>

Options:

  • 0 — maf

Default: 0

Number of Components. [number]

<put parameter description here>

Default: 0

Normalize. [boolean]

<put parameter description here>

Default: True

Çıktılar

Output Image [raster]
<put output description here>
Transformation matrix output [file]
<put output description here>

Konsol kullanımı

processing.runalg('otb:dimensionalityreductionmaf', -in, -method, -nbcomp, -normalize, -out, -outmatrix)

Ayrıca bakınız

BoyutAzaltma (napca)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Algorithm [selection]

<put parameter description here>

Options:

  • 0 — napca

Default: 0

Set the x radius of the sliding window. [number]

<put parameter description here>

Default: 1

Set the y radius of the sliding window. [number]

<put parameter description here>

Default: 1

Number of Components. [number]

<put parameter description here>

Default: 0

Normalize. [boolean]

<put parameter description here>

Default: True

Çıktılar

Output Image [raster]
<put output description here>
`` Inverse Output Image`` [raster]
<put output description here>
Transformation matrix output [file]
<put output description here>

Konsol kullanımı

processing.runalg('otb:dimensionalityreductionnapca', -in, -method, -method.napca.radiusx, -method.napca.radiusy, -nbcomp, -normalize, -out, -outinv, -outmatrix)

Ayrıca bakınız

Boyutİndirgeme (pca)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Algorithm [selection]

<put parameter description here>

Options:

  • 0 — pca

Default: 0

Number of Components. [number]

<put parameter description here>

Default: 0

Normalize. [boolean]

<put parameter description here>

Default: True

Çıktılar

Output Image [raster]
<put output description here>
Inverse Output Image [raster]
<put output description here>
Transformation matrix output [file]
<put output description here>

Konsol kullanımı

processing.runalg('otb:dimensionalityreductionpca', -in, -method, -nbcomp, -normalize, -out, -outinv, -outmatrix)

Ayrıca bakınız

Mean Shift filtering (can be used as Exact Large-Scale Mean-Shift segmentation, step 1)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Spatial radius [number]

<put parameter description here>

Default: 5

Range radius [number]

<put parameter description here>

Default: 15

Mode convergence threshold [number]

<put parameter description here>

Default: 0.1

Maximum number of iterations [number]

<put parameter description here>

Default: 100

Range radius coefficient [number]

<put parameter description here>

Default: 0

Mode search. [boolean]

<put parameter description here>

Default: True

Çıktılar

Filtered output [raster]
<put output description here>
Spatial image [raster]
<put output description here>

Konsol kullanımı

processing.runalg('otb:meanshiftfilteringcanbeusedasexactlargescalemeanshiftsegmentationstep1', -in, -spatialr, -ranger, -thres, -maxiter, -rangeramp, -modesearch, -fout, -foutpos)

Ayrıca bakınız

Yumuşatma (anidif)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Available RAM (Mb) [number]

<put parameter description here>

Default: 128

Smoothing Type [selection]

<put parameter description here>

Options:

  • 0 — anidif

Default: 2

Time Step [number]

<put parameter description here>

Default: 0.125

Nb Iterations [number]

<put parameter description here>

Default: 10

Çıktılar

Output Image [raster]
<put output description here>

Konsol kullanımı

processing.runalg('otb:smoothinganidif', -in, -ram, -type, -type.anidif.timestep, -type.anidif.nbiter, -out)

Ayrıca bakınız

Yumuşatma (gauss)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Available RAM (Mb) [number]

<put parameter description here>

Default: 128

Smoothing Type [selection]

<put parameter description here>

Options:

  • 0 — gaussian

Default: 2

Radius [number]

<put parameter description here>

Default: 2

Çıktılar

Output Image [raster]
<put output description here>

Konsol kullanımı

processing.runalg('otb:smoothinggaussian', -in, -ram, -type, -type.gaussian.radius, -out)

Ayrıca bakınız

Yumuşatma (ortalama)

Tanım

<put algorithm description here>

Parametreler

Input Image [raster]
<put parameter description here>
Available RAM (Mb) [number]

<put parameter description here>

Default: 128

Smoothing Type [selection]

<put parameter description here>

Options:

  • 0 — mean

Default: 2

Radius [number]

<put parameter description here>

Default: 2

Çıktılar

Output Image [raster]
<put output description here>

Konsol kullanımı

processing.runalg('otb:smoothingmean', -in, -ram, -type, -type.mean.radius, -out)

Ayrıca bakınız