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

Exercise 6 (cont.)Exercise 6 (cont.)

Examine the Orthorectification ResultsExamine the Orthorectification Results• Tools → Link Displays → Link

• Notice the difference in geometry, especially in the upper right corner of the two images. That is the result of the orthorectification process