Environments | PYTHON :: EASI :: MODELER |
Batch Mode | Yes |
Quick links | Description :: Parameters :: Parameter descriptions :: Details :: Acknowledgements :: References :: Related |
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Name | Type | Length | Value range |
---|---|---|---|
Input File Name | String | 0 - | |
Input Spectral Library File | String | 0 - | |
Output Spectral Library File | String | 0 - | |
Spectral Library File Format | String | 0 - 1 | SPCB | XLS | TXT Default: SPCB |
Valid Bands Only | String | 0 - 1 | YES | NO Default: NO |
Spectrum Filter Type | String | 0 - 1 | GAU | MED Default: GAU |
Filter Width | Float | 0 - 1 | 0.0 - Default: 30.0 |
Wavelength List 1 | Float | 0 - 16 | |
Wavelength List 2 | Float | 0 - 16 |
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Input File Name
Specifies the name of the file that contains the data set to smooth.
The stored pixel values are smoothed; radiometric transformations in the image metadata are ignored.
If an input (SPECFILI) or output (SPECFILO) spectral library file is specified, this parameter cannot be specified.
Input Spectral Library File
Specifies the name of the spectral library file that contains the spectra to be smoothed.
If an input file (FILE) is specified, this parameter cannot be specified.
Output Spectral Library File
Specifies the name of the spectral library file to be created to receive the smoothed sepctra.
If an input file (FILE) is specified, this parameter cannot be specified.
Spectral Library File Format
Specifies the file format of the output spectral library file.
Valid Bands Only
Specifies whether the selected bands are to be restricted to those with 'plot' or 'bmask' (begin mask) quality values.
This parameter has no effect if the input file contains no band-validity metadata.
Spectrum Filter Type
Specifies the type of filter to use for filtering the band vectors.
Filter Width
Specifies the filter width, in nanometers. The default is 30nm. For a Gaussian convolution filter, the width is the standard deviation of the Gaussian function.
Wavelength List 1
Specifies, in nanometers, the start of each wavelength interval within which smoothing is to be performed.
If this parameter is not specified, the spectra are smoothed across their full wavelength range.
If this parameter is specified, WLEN2 must also be specified.
Wavelength List 2
Specifies, in nanometers, the end of each wavelength interval within which smoothing is to be performed.
If this parameters is not specified, the spectra are smoothed across their full wavelength range
If this parameter is specified, WLEN1 must also be specified.
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Spectrum values within the wavelength intervals specified with WLEN1 and WLEN2 (or across the full wavelength range of the spectra) are smoothed either by convolution with a one-dimensional Gaussian kernel (SPFILT="GAU") or by applying a one-dimensional median filter (SPFILT="MED"). The width of the filter is defined by the FWIDTH parameter; in general, the larger the filter, the greater the degree of smoothing.
In the case of a Gaussian convolution filter, the value of FWIDTH is the standard deviation of the Gaussian function. In the case of a median filter, FWIDTH is the overall neighborhood dimension.
SMSPEC may be used to subdue artifacts in reflectance images or spectra caused by some form of radiometric distortion in the corresponding radiance images or spectra before atmospheric correction. An example of such distortion is spectral line curvature, or 'smile'.
If the noise to be removed from the spectra is in the form of sharp impulses or spikes, the median filter may suppress them while causing less distortion than the Gaussian filter. If the noise is in the form of relatively broad ripples, the Gaussian filter may produce a more acceptable result.
If SMSPEC is applied to an image data set (to smooth along the band dimension), it smoothes the stored pixel values, not the values resulting from the application of any radiometric transformation stored in the image metadata.
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PCI Geomatics received financial support from the Canadian Space Agency/L'Agence Spatiale Canadienne through the Earth Observation Application Development Program (EOADP) for the development of this software, under contract 9F028-0-4914/09.
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Landgrebe, D.A., "Information Extraction Principles and Methods for Multispectral and Hyperspectral Image Data," Chapter 1 of Information Processing of Remote Sensing, World Scientific Publishing Co., River Edge N.J.
Szeredi T., Staenz K., Neville R.A., Canada Centre for Remote Sensing, 1999, "Automatic Endmember Selection: Part I, Theory," submitted to Remote Sensing of the Environment, Elsevier Science, Feb. 1999
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