User Manual - pancroma

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IndexAJISANE Algorithm, 75Anaglyph, 215ASTER, 96ASTER Point Spectrum Generator TM ,229ASTER Spectral Analyzer TM , 246ASTER surface temperatures, 193Batch File Processing, 87, 90Batch Subsetting, 45Change Distance TM , 272, 279Cloud Mask, 129Compute Color Coverage, 3, 218,219Coordinate Display, 21Creating Masks using SpectralAnalysis, 255, 260Dark Area Method, 141Digital Globe, 104Display, 26Distance Fraction TM , 255, 257Downloading Data, 19ELIN, 83ENHG Algorithm, 65ENHG with AJISANE, 383EO-1 ALI, 101EO1-ALI/Hyperion Point SpectrumGenerator TM , 230, 233Euclidean Distance, 171, 248, 249,251, 253, 255, 260, 261, 262, 265Euclidean Distance SpectralAnalyzer TM , 248Exponential, 297Fast HSI, 50Features, 9FFT, 10, 283, 284, 285, 286, 288,290, 292FFT Image Analysis, 283File I/O, 22Formosat-2, 98, 99Gamma correction, 169, 172Gap Filling, 127, 129, 168, 320, 330,337Gaussian Deconvolution, 291Gaussian Low Pass Filter, 290GeoEye®, 6, 7, 22, 109Getting Started, 13GLOVIS, 101, 110, 113, 243, 321Hayes Method, 330Haze Optimized Transform, 145,146, 147Haze Reduction, 141, 142, 145, 146,147, 349, 366, 371Haze Reduction – DEM Method, 149Histogram, 56, 57, 58, 60, 61, 62,63, 105, 165, 168, 169, 170, 173,308, 314HSI, 9, 48, 49, 50, 51, 56, 63, 66, 69,70, 71, 74, 75, 83, 85, 103, 162,245, 308, 313, 314, 315, 347, 360,361, 362, 363, 365, 376, 377, 384,386Huge Files, 302Image Preprocessing, 168Image Processing Utilities, 154, 158,160, 162Image Registration, 136Image Subsetting, 37Index File, 298Installation, 12Landsat 8 Data Sets, 16Landsat 8 Top of AtmosphereReflectance, 188Landsat Approximate SurfaceReflectance, 184Landsat Data Sets, 14Landsat DN Point SpectrumGenerator TM , 220Landsat GEOCOVER, 112Landsat Reflectance Point SpectrumGenerator TM , 226, 228Landsat Reflectance/TIR Band PointSpectrum Generator TM , 228, 229Landsat Spectral Analyzer TM , 235Landsat Surface Reflectance, 110Landsat Surface Temperature, 187,188, 189Landsat Top of AtmosphereReflectance, 179, 201, 240MODIS, 96, 124, 125, 233, 248Moffat, 293, 295, 296, 297397
Multiple Linear Regression, 205Multispectral Band ImageClassification, 279, 282NAIP, 117, 121, 230, 246NAPP, 122NIR, 14, 15, 42, 50, 55, 65, 69, 70,71, 74, 75, 83, 90, 98, 99, 102,109, 131, 141, 197, 198, 199, 221,228, 232, 238, 243, 245, 246, 345,347, 355, 359, 361, 362, 374, 376,381, 385, 386noise, 292, 293, 294, 295Pan Sharpen Gap Filled Images, 345Pan Sharpening, 47, 50, 52, 57, 66,69, 71, 74, 75, 78, 95, 107, 154,165, 302, 308, 313, 315, 318, 354,360, 362, 363, 365, 377Pan Sharpening an Image, 47Point Spectrum Zoom Tool, 233Quick Start, 30QuickBird Imagery, 107RapidEye, 10, 126, 196, 197, 233,248Red Blue Anaglyph, 215Resizing, 167, 168, 171RGB Color Composite PointSelection, 231SAA, 257, 259Scan Line Corrector, 136, 320scatter plot, 145, 202Shadow Reduction, 209Six File Automatic Method, 327SLC, 7, 9, 127, 136, 320, 321, 341,342, 347, 356Spectra, 263, 266SPECTRAL, 10, 50, 51, 78, 79, 81,82, 372Spectral Analysis, 220Spectral Angle, 258Spectral Angle Analysis, 257Spectral Unmixing, 10, 266, 268, 272SPOT, 92SPOT Spectral Analyzer TM , 245, 246SPOT Top of AtmosphereReflectance, 191, 196SPOT vegetation data, 123System Requirements, 11Tasseled Cap Transformation, 199TERAS, 9, 127, 128, 337, 342, 344TIR, 10, 110, 129, 130, 147, 171,172, 187, 191, 221, 228, 229, 238,239, 243, 249, 260, 261, 265, 266Transfer method, 127, 128, 330,331, 332Unsupervised Classification, 212<strong>User</strong> Interface, 29USGS DOQQ, 122Workflow, 356World View 2 Point SpectrumGenerator TM , 230, 233WorldView 2 Top of AtmosphereReflectance, 195WorldView2 Imagery, 104WorldWind, 117XIONG Algorithm, 70, 71, 74, 90X-Y Band Scatter Plots, 202Zoom, 26, 233, 2341
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1. What Is PANCROMA TM ? ..........
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Compute Single Histogram...........
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67. Tutorial - Pan Sharpening Full
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2. What Useful Things Can PANCROMA
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4. PANCROMA TM Features____________
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5. System Requirements_____________
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7. Getting Started_________________
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Each color and NIR band channel con
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determine if one number is differen
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will be shown at the bottom of the
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12. File I/O_______________________
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13. System Variables_______________
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14. Display________________________
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15. The PANCROMA User Interface____
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not find this file , you will be pr
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If you check the ‘Generate Graysc
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19. Image Subsetting_______________
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IMPORTANT NOTE: There is a check bo
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IMPORTANT NOTE: Saving and opening
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When the Input Box becomes visible,
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20. Batch Subsetting_______________
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21. Quick Start - Pan Sharpening an
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During the internal processing of t
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is unlikely that the settings will
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The default method is checked. The
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around 4000 rows by 4000 columns. I
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the ‘Pan Sharpening Pre Processin
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lowerLimit upperLimitThe following
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Another type of unwanted artifact i
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matching algorithm to be applied. T
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25. ENHG Algorithm - Manual Method_
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The next image is the result of pan
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26. ENHG Algorithm - Automatic Meth
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Next, compute the XIONG file. Open
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The XIONG algorithm is one of the m
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29. AJISANE Algorithm______________
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An example of a pan sharpened image
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The spectral match is indicated by
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You must be careful when selecting
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31. ELIN Local Optimization Algorit
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IMPORTANT NOTE: Regions of high con
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Add the green band and the red band
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33. Pan Sharpen Batch File Processi
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34. Working with SPOT® Data_______
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the special image processing utilit
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35. Working with ASTER Data________
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36. Working with Formosat-2 Data___
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100
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ALI data is similar to Landsat with
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38. Working with Digital Globe® Da
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spectral transmission of the telesc
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ow. Make sure you check this before
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40. Working with Landsat Surface Re
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41. Working with Landsat GEOCOVER D
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foreground and background applicati
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GEOCOVER can offer a very attractiv
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After navigation and selecting your
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Although not designed as a data sou
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44. Working with USGS DOQQ and NAPP
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46. Working with MODIS Surface Refl
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47. Working with RapidEye Data_____
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The Transfer method processes the f
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using the PANCROMA TM ‘Preprocess
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and band 5 (MIR) also be input. Thi
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134
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50. Automatic Image Registration of
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The next two images are the registe
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At the present time, PANCROMA TM ca
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Since only a portion of EMR reachin
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144
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‘File’ | ‘Open’. After your
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Haze reduction may be useful in con
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Save your image using GeoTiff file
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The correction is made according to
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54. Image Processing Utilities - Gr
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Input Channel Adjust Group Utility
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55. Image Processing Utilities - SP
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56. Image Processing Utilities - AS
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57. Image Processing Utilities - Pa
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Channel Level AdjustPANCROMA TM pro
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ENHG Scale FactorThe ENHG slider ba
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59. Image Preprocessing____________
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select ‘File’ | ‘Open’ and
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Analyzer. Doubling is done by first
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high pixel brightness in one image
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There are a few rules of thumb rega
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You will need three control points
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• image resampling• geometric m
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ROWS groupsFirst row of dataSecond
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Where QCAL are the calibrated image
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When you select ‘OK’ the surfac
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The rendering below shows a color t
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Q cal = Quantized and calibrated st
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A section of a SPOT metadata file s
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Temperature (measured in degrees Ke
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Calibration requires multiplication
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NIR band, band 2 (green) and band 3
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and 1 (Brightness, a measure of soi
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X-Y Band Scatter PlotsA scatter plo
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presented. Check the ‘Compute Lin
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PANCROMA TM has a utility for regre
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60. Image Post Processing__________
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You can adjust weighting factors fo
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Unsupervised ClassificationUnsuperv
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214
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Grayscale and Color Image TilingIt
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GeoreferencingPANCROMA TM has a uti
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61. Spectral Analysis______________
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When you click ‘OK’, the select
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The plot shows all of the computed
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PANCROMA TM computed that the cover
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Landsat Reflectance Point Spectrum
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SPOT ® Point Spectrum Generator TM
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will become disabled and the Color
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When the ‘Zoom Disabled’ radio
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Digital spectra are recorded for mi
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The next step is to overlay the Lan
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http://www.science.aster.ersdac.or.
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Although the run was not successful
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The pan sharpened image was created
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Now select ‘Spectral Analysis’
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RapidEye ® Spectral Analyzer TMSpe
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Click ‘OK’. The TOA Reflectance
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The second plot is shown below, dis
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have to rationalize the file sizes.
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Euclidean Distance Fraction TM Anal
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The idea is to adjust the included
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In addition to Landsat 7, Spectral
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Low numbers mean high discriminatio
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Copyright USGSAlthough this data is
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Note that the band 6 (TIR) track ba
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higher (whiter) the grayscale pixel
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The table with the manually input r
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this does not correspond to physica
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L71005068_06820030919_B10.TIFL71005
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L71005068_06820040804_B50.TIFL71005
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278
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The parameters are as follows:Compu
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Object Oriented ClassificationPANCR
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to the other. For example a filter
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carefully. PANCROMA TM is able to p
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Landsat imageImage magnitude spectr
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Considerable smoothing has occurred
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IMPORTANT NOTE: In reality, the con
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The following is an example of an i
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In order to deconvolve using fixed
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63. Writing an Index File for an SR
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It will be saved as a .dat file. A
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64. Processing Huge Files and File
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My area of interest for this image
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306
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Now we will start the pan sharpenin
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66. Tutorial - Pan Sharpened Image
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The next step will be to create an
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The panchromatic image is the one i
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And my result looked like this:As y
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67. Tutorial - Pan Sharpening Full
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68. Tutorial - Gap Filling using Tr
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You can use the 'Max Cloud' drop do
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'Enter' and the Adjust file will be
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326
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PANCROMA TM does the rest after tha
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70. Tutorial - Gap Filling using Ha
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Another reason to keep the Search E
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Gap Filled Grayscale ImageGap Fille
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When you do so a batch processing d
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The images below show subsets taken
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340
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It is also apparent that the graysc
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73. Tutorial - Six File TERAS Batch
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Page 351 and 352: Use the checked image processing ut
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Page 359 and 360: From Next PageSection 13Subset One
Page 361 and 362: I again selected ‘Close Graphic I
Page 363 and 364: I then selected ‘Pan Sharpening
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Page 369 and 370: acquired during different seasons o
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Page 373 and 374: I also prepared an image using the
Page 375 and 376: Full sized Landsat scenes can be pr
Page 377 and 378: 78. Tutorial - Improving Image Qual
Page 379 and 380: The following image is the RGB colo
Page 381 and 382: Press ‘OK’. The transformed gra
Page 383 and 384: However it is close enough to illus
Page 385 and 386: The second image is a straightforwa
Page 387 and 388: It is also possible to combine the
Page 389 and 390: 80. Pan Sharpened Image: Landsat Mo
Page 391 and 392: 82. Pan Sharpened Image: Landsat De
Page 397: 88. Pan Sharpened Image: EO-1 Mount
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