DomainTransform¶
域变换在小波和傅立叶变换中的应用
描述¶
域变换在小波和傅里叶变换中的应用。
参数¶
Input Image -in image Mandatory
This will take an input image to be transformed image. For FFT inverse transform, it expects a complex image as two-band image in which the first band represents the real part and second band represents the imaginary part.
Output Image -out image [dtype] Mandatory
This parameter holds the output file name to which transformed image will be written. This has a slightly different behaviour depending on transform type.
For Wavelet, output is a single band image for both forward and inverse transform. For FFT forward transform, output is two band image where first band represents real part and second band represents imaginary part of a complex image.
Mode -mode [fft|wavelet] Default value: wavelet
This parameter allows one to select between fft(fourier) and wavelet
- FFT transform
FFT transform - Wavelet
Wavelet transform
FFT变换选项¶
Shift fft transform -mode.fft.shift bool Default value: false
Shift transform of fft filter
小波选项¶
Select wavelet form -mode.wavelet.form [haar|db4|db6|db8|db12|db20|sb24|sb44|sym8] Default value: haar
- HAAR
- DAUBECHIES4
- DAUBECHIES6
- DAUBECHIES8
- DAUBECHIES12
- DAUBECHIES20
- SPLINE_BIORTHOGONAL_2_4
- SPLINE_BIORTHOGONAL_4_4
- SYMLET8
Number of decomposition levels -mode.wavelet.nlevels int Default value: 2
Number of decomposition levels
Direction -direction [forward|inverse] Default value: forward
- Forward
- Inverse
Available RAM (MB) -ram int Default value: 256
Available memory for processing (in MB).
实例¶
从命令行执行以下操作：
otbcli_DomainTransform -in input.tif -mode.wavelet.form haar -out output_wavelet_haar.tif
来自Python的评论：
import otbApplication
app = otbApplication.Registry.CreateApplication("DomainTransform")
app.SetParameterString("in", "input.tif")
app.SetParameterString("mode.wavelet.form","haar")
app.SetParameterString("out", "output_wavelet_haar.tif")
app.ExecuteAndWriteOutput()
局限性¶
此应用程序未流式处理，请在处理大图像时检查您的系统资源