FTLOC

Locate spectrally flat targets


EnvironmentsPYTHON :: EASI :: MODELER
Batch ModeYes
Quick linksDescription :: Parameters :: Parameter descriptions :: Details :: Related

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Description


FTLOC searches an input multiband image for pixel locations corresponding to the 'flattest' image-derived spectra. By definition, a relatively flat spectrum is better approximated (in a root mean square error sense) by a polynomial function of wavelength, of user-specified order. The user-specified N pixel locations with the flattest spectra are indicated in an output bitmap. FTLOC requires the presence of response profile metadata in the input image data set.
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Parameters


Name Type Length Value range
Training Site Window Integer 0 - 4 Xoffset, Yoffset, Xsize, Ysize
InputBitmap: Input training site Bitmap port 0 - 1  
OutputBitmap: Output bitmap Bitmap port 0 - 1  
Order of Polynomial Function Integer 0 - 1 1 - 4
Default: 2
Number of Locations to Indicate Integer 0 - 1 0 -
Default: 10
Radiometric Transformation Level Integer 0 - 1  
Input: Input raster channel(s) Raster port 0 - 1024  
Wavelength Interval Float 0 - 2  
Valid Bands Only String 0 - 1 YES | NO
Default: NO
Report String 0 - 192 See parameter description
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Parameter descriptions

Training Site Window

Optionally specifies a rectangular window (Xoffset, Yoffset, Xsize, Ysize) within the input image to which the search will be limited. If this parameter is not specified, the entire image is used by default.

Xoffset, Yoffset define the upper-left starting pixel coordinates of the window. Xsize is the number of pixels that define the window width. Ysize is the number of lines that define the window height.

InputBitmap: Input training site

Optionally specifies a bitmap mask that defines one or more image regions to which the search will be limited.

OutputBitmap: Output bitmap

Specifies an existing bitmap in which the selected locations will be indicated.

Order of Polynomial Function

Specifies the order of the polynomial function of band center wavelength used to approximate the image value spectra. You may specify a value up to order 4; the default is 2.

Number of Locations to Indicate

Specifies number of pixel locations with the flattest image value spectra to indicate in the output bitmap. The default value is 10.

Radiometric Transformation Level

Specifies the radiometric sequence of radiometric transformations already represented in the image metadata that are to be applied to the stored pixel values to generate the image values that will be involved in the computation of the new radiometric transformation.

Options include:

Input: Input raster channel(s)

Specifies a subset of the input channels to which the image band selection is to be restricted. The image metadata indicates which channels store data set bands; the default is all data set band channels.

Wavelength Interval

Specifies a wavelength interval such that only the image bands whose center wavelengths are within the interval are involved in the test for 'flatness'. The interval must contain at least four bands.

For example:

By default, no restrictions are specified.

Valid Bands Only

Specifies whether the selected bands are to be restricted to those identified as 'Valid'.

Valid options are:

If the input file does not contain band-validity metadata, this parameter has no effect.

Note: The assigned strings may contain either uppercase or lowercase letters.

Report

Specifies where to direct the generated report.

Available options are:

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Details

The 'flat' image-derived spectra located using FTLOC can be used to create a radiometric transformation that reduces the presence of atmospheric absorption features in the image data. The transformed image is more suitable for comparison with ground or laboratory measured reflectance spectra than is the original image.

I2SP may be used to derive the individual spectra from the image, using the output bitmap created by FTLOC. These spectra may be examined using the spectra plot panel of CATALYST Professional Focus to determine whether or not their differences are minor and likely due to noise. If so, I2SP should be used to derive the mean spectrum for the bitmap; this spectrum (a 'transformation spectrum') will be used to evaluate a radiometric transformation. If not, the bitmap should be edited in Focus to exclude the outlier spectra, or FTLOC should be run with a smaller value for the number of locations to indicate (NUMLOCS) until the locations of the outlier spectra are omitted.

SP2RT may be used to create a radiometric transformation for the image from the transformation spectrum. The transformation consists of the reciprocal of the spectrum values as the band-specific gains, and an offset of zero.

To directly compare the flat spectrum transformed image with a set of reference reflectance spectra, one of the reference spectra must represent the material in the scene corresponding to the image transformation spectrum. Then, all the reference spectra must be divided by this identified reference spectrum.

The image-derived spectra may still differ from the transformed reference spectra by a gain that is constant over all bands (as well as by artifacts that affect the accuracy of the flat spectrum transformation). This is not important if the image is to be classified on the basis of the reference spectra using the spectral angle mapping technique (SAM).

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