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Image RectificationImage Rectification
Analysis and applications of remote sensing imagery
Instructor: Dr. Cheng-Chien Liu
Department of Earth Sciences
National Cheng Kung University
Last updated: 26 April 2005
Chapter 3Chapter 3
IntroductionIntroduction
Why need Why need Rectification Rectification ((糾正糾正 ))??• Distortion 畸變 Rectification 糾正
Geometric distortion Geometric distortion 幾何畸變幾何畸變• Altitude, attitude, velocity of sensor platform
• Panoramic distortion, earth curvature, atmospheric refraction, relief displacement, nonlinearities in the sweep of a sensor’s IFOV
Geometric correctionGeometric correction
Two-step procedureTwo-step procedure• Systematic (predictable)
e.g. eastward rotation of the earth skew distortion Deskewing offest each successive scan line slightly to the west
parallelogram image
• Random (unpredictable)e.g. random distortions and residual unknown systematic
distortionsGround control points (GCPs)
Highway intersections, distinct shoreline features,… Two coordinate transformation equations
Distorted-image coordinate Geometrically correct coordinate
Two coordinate transformation Two coordinate transformation equationsequations
Affine coordinate transformAffine coordinate transform• Six factors
• Transformation equationx = a0 + a1X + a2Y
y = b0 + b1X + b2Y (x, y): image coordinate (X, Y): ground coordinate
• Six parameters six conditions 3 GCPs
• If GCPs > 3 redundancy LS solutions
ResamplingResampling
ResamplingResampling• Fig 7.1: Resampling process
Transform coordinateAdjust DN value perform after classification
• MethodsNearest neighborBilinear interpolationBicubic convolution
Resampling (cont.)Resampling (cont.)
Nearest neighborNearest neighbor• Fig 7.1: a a΄ (shaded pixel)
• Fig C.1: implementRounding the computed coordinates to the nearest whole
row and column number
• AdvantageComputational simplicity
• DisadvantageDisjointed appearance: feature offset spatially up to ½ pixel
(Fig 7.2b)
Resampling (cont.)Resampling (cont.)
Bilinear interpolationBilinear interpolation• Fig 7.1: a, b, b, b a΄ (shaded pixel)
Takes a distance-weighted average of the DNs of the four nearest pixels
• Fig C.2a: implementEq. C.2Eq. C.3
• AdvantageSmoother appearing (Fig 7.2c)
• DisadvantageAlter DN valuesPerformed after image classification procedures
Resampling (cont.)Resampling (cont.)
Bicubic (cubic) interpolationBicubic (cubic) interpolation• Fig 7.1: a, b, b, b, c, … a΄ (shaded pixel)
Takes a distance-weighted average of the DNs of the four nearest pixels
• Fig C.2b: implementEq. C.5Eq. C.6Eq. C.7
• Advantage (Fig 7.2d)Smoother appearingProvide a slightly sharper image than the bilinear interpolation image
• DisadvantageAlter DN valuesPerformed after image classification procedures
Exercise 1Exercise 1
Georeferenced Data and Image-Map Georeferenced Data and Image-Map • Construct an image-map complete with map grids and
annotation, and produce an output image Start ENVIStart ENVI Open and Display SPOT DataOpen and Display SPOT Data
• bldr_reg subdirectory: bldr_sp.img Edit Map Info in ENVI HeaderEdit Map Info in ENVI Header Edit Map InformationEdit Map Information
• The basic map information used by ENVI in georeferencing.• Click on the arrow next to the Projection/Datum field• Click on the active DMS or DDEG button
Cursor Location/ValueCursor Location/Value
Exercise 1 (cont.)Exercise 1 (cont.)
Overlay Map GridsOverlay Map Grids• Overlay →Grid Lines.• File →Restore Setup• file bldr_sp.grd• Options →Edit Map Grid Attributes• Options →Edit Geographic Grid Attributes• Apply
Overlay Map AnnotationOverlay Map Annotation• Overlay →Annotation• File →Restore Annotation• file bldr_sp.ann• Object
Output to Image or PostscriptOutput to Image or Postscript Direct PrintingDirect Printing
Exercise 2Exercise 2
Image to Image RegistrationImage to Image Registration• The georeferenced SPOT image will be used as the Base image, and a pixel-based
Landsat TM image will be warped to match the SPOT. Open and Display Landsat TM Image FileOpen and Display Landsat TM Image File
• bldr_reg directory: file bldr_tm.img• Band 3
Display the Cursor Location/ValueDisplay the Cursor Location/Value Start Image Registration and Load GCPsStart Image Registration and Load GCPs
• Map → Registration → Select GCPs:• Base Image: Display #1 (the SPOT image)• Warp Image: Display #2 (the TM image).• SPOT image to 753, 826• TM image to 331, 433• Add Point• Show List• Try this for a few points to get the feel of selecting GCPs. Once you have at least 4
points, the RMS error is reported.• Options → Clear All Points to clear all of your points.
Exercise 2 (cont.)Exercise 2 (cont.)
File → Restore GCPs from ASCII.File → Restore GCPs from ASCII.• file name bldr_tm.pts
Working with GCPsWorking with GCPs On/OffOn/Off
• Delete• Update• Predict
Warp ImagesWarp Images• Options → Warp• Displayed Band.
Warp MethodWarp Method• RST• Resampling• Nearest Neighbor• filename bldr_tm1.wrp• repeat steps 1 and 2 still using RST warping but with both Bilinear, and Cubic Convolution resampling
methods.• Output the results to bldr_tm2.wrp and bldr_tm3.wrp, respectively.• Repeat steps 1 and 2 twice more, this time performing a 1st degree Polynomial warp using Cubic
Convolution resampling, and again using a Delaunay Triangulation warp with Cubic Convolution resampling.
• Output the results to bldr_tm4.wrp and bldr_tm5.wrp, respectively.
Exercise 2 (cont.)Exercise 2 (cont.)
Compare Warp ResultsCompare Warp Results• Tools → Link → Link Displays• Load bldr_tm2.wrp and bldr_tm3.wrp into new displays and
use the image linking and dynamic overlays to compare the effect of the three different resampling methods: nearest neighbor, bilinear interpolation, and cubic convolution.
• Note how jagged the pixels appear in the nearest neighbor resampled image. The bilinear interpolation image looks much smoother, but the cubic convolution image is the best result, smoother, but retaining fine detail.
Examine Map CoordinatesExamine Map Coordinates Tools → Cursor Location/ValueTools → Cursor Location/Value Close All FilesClose All Files
Exercise 3Exercise 3
Image to Map RegistrationImage to Map Registration• The map coordinates picked from the georeferenced
SPOT image and a vector Digital Line Graph (DLG) will be used as the Base, and the pixel-based Landsat TM image will be warped to match the map data.
Open and Display Landsat TM Image FileOpen and Display Landsat TM Image File• File → Open Image File.• bldr_reg directory: file bldr_tm.img• Gray Scale• Band 3
Exercise 3 (cont.)Exercise 3 (cont.)
Select Image-to-Map Registration and Restore GCPsSelect Image-to-Map Registration and Restore GCPs• Map → Registration → Select GCPs:• Image to Map• UTM• enter 13 in the Zone text field.• Leave the pixel size at 30 m and click OK to start the registration.• Add Individual GCPs by moving the cursor position in the warp image to a
ground location for which you know the map coordinate (either read from a map or ENVI vector file [see the next section]).
• Enter the known map coordinates manually into the E (Easting) and N (Northing) text boxes and click Add Point to add the new GCP.
File → Restore GCPs from ASCII File → Restore GCPs from ASCII • file bldrtm_m.pts.• Show List
Exercise 3 (cont.)Exercise 3 (cont.)
Select Image-to-Map Registration and Restore GCPsSelect Image-to-Map Registration and Restore GCPs• Add Map GCPs Using Vector Display of DLGs• File → Open Vector File → USGS DLG.• bldr_rd.dlg• Memory• ROADS AND TRAILS:• BOULDER, CO file in the Available Vectors Layers• Load Selected• New Vector Window• Click and drag the left mouse button in the Vector Window #1 to activate a
crosshair cursor.• Tools → Pixel Locator• 402, 418• Apply.• In the Vector Window 477593.74, 4433240.0 • Select Export Map Location. The new map coordinates will appear in the Ground
Control Points Selection dialog.• Add Point• observe the change in RMS error
Exercise 3 (cont.)Exercise 3 (cont.)
RST and Cubic Convolution WarpRST and Cubic Convolution Warp• Options →Warp File• file name bldr_tm.img • select all 6 TM bands for warping.• Warp Method RST• Resampling Cubic Convolution• background value 255• output file name bldrtm_m.img
Display Result and EvaluateDisplay Result and Evaluate Close Selected FilesClose Selected Files
Self testSelf test
Conduct the image-to-image registrationConduct the image-to-image registration• Base image:
C:\RSI\IDL60\examples\data\afrpolitsm.png
• Warp image:C:\RSI\IDL60\examples\data\africavlc.png
• Pay special attention toSelection of GCPsNo of GCPsValue of RMSMethod of warping
• Examine your result by linking two displays with 50% transparency
OrthorectificationOrthorectification
OrthorectificationOrthorectification• Definition
The geometry of an image is made planimetric (map-accurate) by modeling the nature and magnitude of geometric distortions in the imagery
• StepsBuild the interior orientation (aerial photograph only)Build the exterior orientationOrthorectify using a Digital Elevation Model (DEM)
Exercise 4Exercise 4
Orthorectify the airphoto of Cha-Yi areaOrthorectify the airphoto of Cha-Yi area• Raw image: 88R56151.tif• Build the interior orientation
Focal Length and fiducial pairs: RMK-TOP30-AF.cam
• Build the exterior orientationImage of GCPs: DETAIL directoryCoordinates of GCPs: xyz.con
• Orthorectify using a Digital Elevation ModelDEM file: dtm_40m.tifInterpolation: 40m → 4m
• Accuracy of orthoimageCheck pointsOverlay vector files
Exercise 5Exercise 5
Georeferencing Images Using Input Georeferencing Images Using Input GeometryGeometry• Modern sensors → detailed acquisition (platform
geometry) information → model-based geometric rectification and map registration
• Users must have the IGM or GLT file as a minimum to conduct this form of geocorrection The Input Geometry (IGM) file: the X and Y map coordinates for a
specified map projection for each pixel in the uncorrected input image.The Geometry Lookup (GLT) file: the sample and line that each pixel
in the output image came from in the input image. If the GLT value is positive, there was an exact pixel match. If the GLT value is negative,
there was no exact match and the nearest neighboring pixel is used
Exercise 5 (cont.)Exercise 5 (cont.)
Uncorrected HyMap Hyperspectral DataUncorrected HyMap Hyperspectral Data• HyMap
Aircraft-mounted commercial hyperspectral sensor 126 spectral channels covering the 0.44 - 2.5 m range with approximately 15nm spectral
162 resolution and 1000:1 SNR over a 512-pixel swath. Spatial resolution is 3-10 m Gyro-stabilized platform
• Open HyMap data envidata/cup99hym directory File: cup99hy_true.img Examine Uncorrected Data
Cursor Location/Value
• Examine IGM files envidata/cup99hym directory File: cup99hy_geo_igm Available Bands List dialog Gray Scale IGM Input X Map New Display IGM Input Y Map New Display
Exercise 5 (cont.)Exercise 5 (cont.)
Uncorrected HyMap Hyperspectral Data (cont.)Uncorrected HyMap Hyperspectral Data (cont.)• Geocorrect Image Using IGM File
Map →Georeference from Input Geometry →Georeference from IGM File: cup99hy.eff Input Data File File: cup99hy.eff Spectral Subset File Spectral Subset: band 109
Input Data File Input X Geometry Band: IGM Input X Map Input Y Geometry Band: IGM Input Y Map
Geometry Projection Information UTM, Zone 13, datum: North America 1927
the same map projection as the input geometry. Build Geometry Lookup File Parameters
background value of -9999, output filename Display and Evaluate Correction Results
Available Bands List Georef band Cursor Location/Value
Examine GLT Files GLT Sample Look-up GLT Line Look-up
Exercise 5 (cont.)Exercise 5 (cont.)
Geocorrect Image using GLT FileGeocorrect Image using GLT File• Map →Georeference from Input Geometry
→Georeference from GLTInput Geometry Lookup File: cup99hy_geo_gltInput Data File: cup99hy.eff
Spectral Subset File Spectral Subset: band 109 Input Data File Georeference from GLT Parameters -9999 output filename
Display and Evaluate Correction Results Available Bands List Georef band. Cursor Location/Value
Exercise 5 (cont.)Exercise 5 (cont.)
Using Build GLT with Map ProjectionUsing Build GLT with Map Projection• File →Open Image
File: cup99hy_geo_igmInput X Geometry Band
IGM Input X Map
Input Y Geometry Band IGM Input Y Map
• Geometry Projection InformationState Plane (NAD 27)Set Zone Nevada West (2703)Build Geometry Lookup File Parameters
Overlay Map GridsOverlay Map Grids
Exercise 6Exercise 6
IKONOS and QuickBird OrthorectificationIKONOS and QuickBird Orthorectification OrthorectificationOrthorectification
• Use the Rational Polynomial Coefficients (RPCs) provided by the data vendors with some products
• Orthorectification 正射糾正 Open files Open files
• File → Open Image Fileortho subdirectoryFile: po_101515_pan_0000000.tif
• File → Open External File → Digital Elevation → USGS DEMFile: CONUS_USGS.demUSGS DEM Input Parameters dialogoutput filename: ortho_dem.dat New DisplayLoad Band
Exercise 6 (cont.)Exercise 6 (cont.)
Run the OrthorectificationRun the Orthorectification• Map → Orthorectification → Orthorectify IKONOS.
File: po_101515_pan_0000000.tif Enter Orthorectification Parameters dialog Image Resampling: Bilinear Background 0 Input Height
specifies whether a fixed elevation or a DEM (more accurate) value will be used for the entire image ortho_dem.dat
DEM Resampling Bilinear Geoid Offset The height of the geoid above mean sea level in the location of the image.
-35: means that the ellipsoid is about 35 meters above mean sea level in this area Many institutions doing photogrammetric processing have their own software for geoid height determination, or you can
obtain software from NOAA, NIMA, USGS, or other sources. A geoid height calculation can currently be found at the following URL: http://www.ngs.noaa.gov/cgi-bin/GEOID_STUFF/geoid99_prompt1.prl
Save Computed DEM Orthorectified Image
File: ikonos_ortho.dat
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