User Manual - pancroma

More documents

Recommendations

Info

72. Tutorial – Gap Filling using TERAS Method________________________________________________________________The third PANCROMA TM method for filling gaps in Landsat ETM+ images is theTERAS method. TERAS is a modified sliding window, local optimization method.This means that a square frame is established so that the edges of the frame aretwice the user-specified searchRadius in length and width. The frame ispositioned over the first target Digital Number (DN). Computations areconducted to map the gap DNs to the reference image DNs, using only DNswithin the frame. After filling the gaps, the frame is displaced and the process isrepeated.Because the mapping is very localized (for example within a frame of size 20pixels) with respect to the size of the image, the match is only influenced by theDNs in the immediate vicinity of the center target DN. This can result in a highfidelity match between the filled DNs and the DNs adjacent to the gap.Using the TERAS algorithm is similar to the Hayes described above. You startthe filling procedure by opening first the Reference (grayscale) image (the onewith the gaps), followed by the Adjust image. When the images are loaded,select ‘Gap Fill’ | ‘Gap Fill TERAS Method’. A Gap Fill Data Form will appear.You can select the algorithm parameters: Search Extents, the Gap Thresholdand the Cloud Saturation Cutoff. The default values are 20, 1 and 100,respectively. The Search Extents defines the size of the sliding window withinwhich PANCROMA TM will look for similar pixels. PANCROMA TM will search thetarget +/- the Search Extents, so the size of the window is twice the SearchExtents value.The Gap Threshold determines which pixels in the Reference image will becomputed. Any pixel with a brightness value less than the Gap Threshold will beconsidered a missing pixel and PANCROMA TM will attempt to fill it.The Cloud Saturation Cutoff value is designed to minimize cloud pixel“blooming”. This problem is caused when the Adjust (no gap) image has cloudsthat the Reference (gap) image does not. These highly saturated pixels candistort the matching computation and will propagate across the entire slidingwindow frame. In order to avoid this, the algorithm will ignore any pixel with a DNabove the Cloud Saturation Cutoff value in its computations. Note that this willmitigate the phenomenon but may not completely eliminate it.337
The images below show subsets taken from a Reference gap image, thecorresponding filled image, and the Adjust image. The image match very goodfor this example. The corresponding RGB color composite made from the gapfilled images is shown in the fourth image below.338
Page 2 and 3:
1. What Is PANCROMA TM ? ..........
Page 4 and 5:
Compute Single Histogram...........
Page 6 and 7:
67. Tutorial - Pan Sharpening Full
Page 8 and 9:
2. What Useful Things Can PANCROMA
Page 10 and 11:
4. PANCROMA TM Features____________
Page 12 and 13:
5. System Requirements_____________
Page 14 and 15:
7. Getting Started_________________
Page 16 and 17:
Each color and NIR band channel con
Page 18:
determine if one number is differen
Page 21 and 22:
will be shown at the bottom of the
Page 23 and 24:
12. File I/O_______________________
Page 25 and 26:
13. System Variables_______________
Page 27:
14. Display________________________
Page 30 and 31:
15. The PANCROMA User Interface____
Page 32:
not find this file , you will be pr
Page 35 and 36:
If you check the ‘Generate Graysc
Page 38 and 39:
19. Image Subsetting_______________
Page 40 and 41:
IMPORTANT NOTE: There is a check bo
Page 42 and 43:
IMPORTANT NOTE: Saving and opening
Page 44 and 45:
When the Input Box becomes visible,
Page 46 and 47:
20. Batch Subsetting_______________
Page 48 and 49:
21. Quick Start - Pan Sharpening an
Page 50 and 51:
During the internal processing of t
Page 52 and 53:
is unlikely that the settings will
Page 54 and 55:
The default method is checked. The
Page 56 and 57:
around 4000 rows by 4000 columns. I
Page 58 and 59:
the ‘Pan Sharpening Pre Processin
Page 60 and 61:
lowerLimit upperLimitThe following
Page 62 and 63:
Another type of unwanted artifact i
Page 64 and 65:
matching algorithm to be applied. T
Page 66 and 67:
25. ENHG Algorithm - Manual Method_
Page 68 and 69:
The next image is the result of pan
Page 70 and 71:
26. ENHG Algorithm - Automatic Meth
Page 72 and 73:
Next, compute the XIONG file. Open
Page 74 and 75:
The XIONG algorithm is one of the m
Page 76 and 77:
29. AJISANE Algorithm______________
Page 78 and 79:
An example of a pan sharpened image
Page 80 and 81:
The spectral match is indicated by
Page 82 and 83:
You must be careful when selecting
Page 84:
31. ELIN Local Optimization Algorit
Page 87 and 88:
IMPORTANT NOTE: Regions of high con
Page 89 and 90:
Add the green band and the red band
Page 91 and 92:
33. Pan Sharpen Batch File Processi
Page 93 and 94:
34. Working with SPOT® Data_______
Page 95 and 96:
the special image processing utilit
Page 97 and 98:
35. Working with ASTER Data________
Page 99 and 100:
36. Working with Formosat-2 Data___
Page 101 and 102:
100
Page 103 and 104:
ALI data is similar to Landsat with
Page 105 and 106:
38. Working with Digital Globe® Da
Page 107 and 108:
spectral transmission of the telesc
Page 109 and 110:
ow. Make sure you check this before
Page 111 and 112:
40. Working with Landsat Surface Re
Page 113 and 114:
41. Working with Landsat GEOCOVER D
Page 115 and 116:
foreground and background applicati
Page 117 and 118:
GEOCOVER can offer a very attractiv
Page 119 and 120:
After navigation and selecting your
Page 121 and 122:
Although not designed as a data sou
Page 123 and 124:
44. Working with USGS DOQQ and NAPP
Page 125 and 126:
46. Working with MODIS Surface Refl
Page 127 and 128:
47. Working with RapidEye Data_____
Page 129 and 130:
The Transfer method processes the f
Page 131 and 132:
using the PANCROMA TM ‘Preprocess
Page 133 and 134:
and band 5 (MIR) also be input. Thi
Page 135 and 136:
134
Page 137 and 138:
50. Automatic Image Registration of
Page 139 and 140:
The next two images are the registe
Page 141 and 142:
At the present time, PANCROMA TM ca
Page 143 and 144:
Since only a portion of EMR reachin
Page 145 and 146:
144
Page 147 and 148:
‘File’ | ‘Open’. After your
Page 149 and 150:
Haze reduction may be useful in con
Page 151 and 152:
Save your image using GeoTiff file
Page 153 and 154:
The correction is made according to
Page 155 and 156:
54. Image Processing Utilities - Gr
Page 157 and 158:
Input Channel Adjust Group Utility
Page 159 and 160:
55. Image Processing Utilities - SP
Page 161 and 162:
56. Image Processing Utilities - AS
Page 163 and 164:
57. Image Processing Utilities - Pa
Page 165 and 166:
Channel Level AdjustPANCROMA TM pro
Page 167 and 168:
ENHG Scale FactorThe ENHG slider ba
Page 169 and 170:
59. Image Preprocessing____________
Page 171 and 172:
select ‘File’ | ‘Open’ and
Page 173 and 174:
Analyzer. Doubling is done by first
Page 175 and 176:
high pixel brightness in one image
Page 177 and 178:
There are a few rules of thumb rega
Page 179 and 180:
You will need three control points
Page 181 and 182:
• image resampling• geometric m
Page 183 and 184:
ROWS groupsFirst row of dataSecond
Page 185 and 186:
Where QCAL are the calibrated image
Page 187 and 188:
When you select ‘OK’ the surfac
Page 189 and 190:
The rendering below shows a color t
Page 191 and 192:
Q cal = Quantized and calibrated st
Page 193 and 194:
A section of a SPOT metadata file s
Page 195 and 196:
Temperature (measured in degrees Ke
Page 197 and 198:
Calibration requires multiplication
Page 199 and 200:
NIR band, band 2 (green) and band 3
Page 201 and 202:
and 1 (Brightness, a measure of soi
Page 203 and 204:
X-Y Band Scatter PlotsA scatter plo
Page 205 and 206:
presented. Check the ‘Compute Lin
Page 207 and 208:
PANCROMA TM has a utility for regre
Page 209 and 210:
60. Image Post Processing__________
Page 211 and 212:
You can adjust weighting factors fo
Page 213 and 214:
Unsupervised ClassificationUnsuperv
Page 215 and 216:
214
Page 217 and 218:
Grayscale and Color Image TilingIt
Page 219 and 220:
GeoreferencingPANCROMA TM has a uti
Page 221 and 222:
61. Spectral Analysis______________
Page 223 and 224:
When you click ‘OK’, the select
Page 225 and 226:
The plot shows all of the computed
Page 227 and 228:
PANCROMA TM computed that the cover
Page 229 and 230:
Landsat Reflectance Point Spectrum
Page 231 and 232:
SPOT ® Point Spectrum Generator TM
Page 233 and 234:
will become disabled and the Color
Page 235 and 236:
When the ‘Zoom Disabled’ radio
Page 237 and 238:
Digital spectra are recorded for mi
Page 239 and 240:
The next step is to overlay the Lan
Page 241 and 242:
http://www.science.aster.ersdac.or.
Page 243 and 244:
Although the run was not successful
Page 245 and 246:
The pan sharpened image was created
Page 247 and 248:
Now select ‘Spectral Analysis’
Page 249 and 250:
RapidEye ® Spectral Analyzer TMSpe
Page 251 and 252:
Click ‘OK’. The TOA Reflectance
Page 253 and 254:
The second plot is shown below, dis
Page 255 and 256:
have to rationalize the file sizes.
Page 257 and 258:
Euclidean Distance Fraction TM Anal
Page 259 and 260:
The idea is to adjust the included
Page 261 and 262:
In addition to Landsat 7, Spectral
Page 263 and 264:
Low numbers mean high discriminatio
Page 265 and 266:
Copyright USGSAlthough this data is
Page 267 and 268:
Note that the band 6 (TIR) track ba
Page 269 and 270:
higher (whiter) the grayscale pixel
Page 271 and 272:
The table with the manually input r
Page 273 and 274:
this does not correspond to physica
Page 275 and 276:
L71005068_06820030919_B10.TIFL71005
Page 277 and 278:
L71005068_06820040804_B50.TIFL71005
Page 279 and 280:
278
Page 281 and 282:
The parameters are as follows:Compu
Page 283 and 284:
Object Oriented ClassificationPANCR
Page 285 and 286:
to the other. For example a filter
Page 287 and 288: carefully. PANCROMA TM is able to p
Page 289 and 290: Landsat imageImage magnitude spectr
Page 291 and 292: Considerable smoothing has occurred
Page 293 and 294: IMPORTANT NOTE: In reality, the con
Page 295 and 296: The following is an example of an i
Page 297 and 298: In order to deconvolve using fixed
Page 299 and 300: 63. Writing an Index File for an SR
Page 301 and 302: It will be saved as a .dat file. A
Page 303 and 304: 64. Processing Huge Files and File
Page 305 and 306: My area of interest for this image
Page 307 and 308: 306
Page 309 and 310: Now we will start the pan sharpenin
Page 311 and 312: 66. Tutorial - Pan Sharpened Image
Page 313 and 314: The next step will be to create an
Page 315 and 316: The panchromatic image is the one i
Page 317 and 318: And my result looked like this:As y
Page 319 and 320: 67. Tutorial - Pan Sharpening Full
Page 321 and 322: 68. Tutorial - Gap Filling using Tr
Page 323 and 324: You can use the 'Max Cloud' drop do
Page 325 and 326: 'Enter' and the Adjust file will be
Page 327 and 328: 326
Page 329 and 330: PANCROMA TM does the rest after tha
Page 331 and 332: 70. Tutorial - Gap Filling using Ha
Page 333 and 334: Another reason to keep the Search E
Page 335 and 336: Gap Filled Grayscale ImageGap Fille
Page 337: When you do so a batch processing d
Page 341 and 342: 340
Page 343 and 344: It is also apparent that the graysc
Page 345 and 346: 73. Tutorial - Six File TERAS Batch
Page 347 and 348: common areas of both scenes. See th
Page 349 and 350: 348
Page 351 and 352: Use the checked image processing ut
Page 353 and 354: IssuesAlthough the gap filling proc
Page 355 and 356: 76. Tutorial - Pan Sharpening Lands
Page 357 and 358: 77. Tutorial - Image Processing Wor
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
Page 365 and 366: the vegetation tones are still norm
Page 367 and 368: Reduction’ and then ‘Apply Cont
Page 369 and 370: acquired during different seasons o
Page 371 and 372: This image is better than the Trans
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 393 and 394:
Page 395 and 396:
Page 397 and 398:
88. Pan Sharpened Image: EO-1 Mount
Page 399:
Multiple Linear Regression, 205Mult
show all

User Manual - pancroma

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?