5B

• Categories of image rectification

  Deterministic & Statistical approach
• Deterministic Approach

  • establishes models for the nature and magnitude of the sources of distortion and uses these models to establish correction formulae.
• Deterministic Approach relies on data of the flight parameters and the terrain information and is effective when the types of distortion are well characterized, such as that caused by earth rotation.
• Statistical Approach

  • Using a GCP data set, it establishes mathematical relationship between image coordinates and their corresponding map coordinates using standard statistical procedures.

   
• Statistical Approach

  • These relationships can be used to correct the image geometry irrespective of the analyst’s knowledge of the source and type of distortion
• Statistical Approach

  • The most widely used method in this category is the polynomial trend mapping (PTM) technique that employs polynomial regression equations to relate image coordinates and their corresponding map coordinates
• Georeferencing refers to assigning map coordinates to image data

  image data may be projected onto the desired plane, but not yet referenced to the proper coordinate system.
• Rectification

  by definition, involves georeferencing, since all map projection systems are associated with map coordinates.
• Image-to-image registration

  involves georeferencing only if the reference image is already georeferenced.
• Georeferencing

  by itself, involves changing only the map coordinate information in the image file.
• Orthorectification

  • form of rectification that corrects for terrain displacement and can be used if there is a DEM of the study area.
• Orthorectification

  • based on collinearity equations, which can be derived by using 3D GCPs
• Orthorectification

  • in relatively flat areas, orthorectification is not necessary, but in mountainous areas (or on aerial photographs of buildings), where a high degree of accuracy is required, orthorectification is recommended.
• Map Projection and Coordinate System

  •Before rectifying the data, one must determine the appropriate coordinate system considering the primary use for the data

  •How large or small an area is mapped?

  • Different projections are intended for different area sizes

  •Where on the globe is the study area?

  • Polar regions and equatorial regions require different projections for maximum accuracy

  •What is the extent of the study area?

  • Circular, north-south, east-west, and oblique areas may all

   require different projection systems
• Transverse Mercator projection

  Ø The UTM system divides the surface of Earth between 80o S latitude and 84oN latitude into 60 zones, each 6o of longitude in width and centered over a meridian of longitude
• Transverse Mercator projection

  Ø  Zones are numbered from 1 to 60
• Transverse Mercator projection

  Ø  Reference longitude: Central meridian of each zone
• Transverse Mercator projection

  Ø  Reference latitude is the Equator
• Transverse Mercator projection

  X-shift, Y-shift; False easting and northing
• Rectification is necessary in cases where the pixel grid of the image must be changed to fit a map projection system or a reference image.

   
• Reasons for rectifying image data:

  ü  comparing pixels scene to scene in applications, such as change detection developing GIS data bases for GIS modeling

  ü  identifying training samples according to map coordinates prior to classification creating accurate scaled photomaps

  ü  overlaying an image with vector data

  ü  comparing images that are originally at different scales

  ü  extracting accurate distance and area measurements

  ü  mosaicking images

  ü performing any other analyses requiring precise geographic locations
• Planar images, that need map coordinate information should only be georeferenced (a much simpler process)

  •In many cases, the image header can simply be updated with new map coordinate information
• Redefining:

  Ø  the map coordinate of the upper left corner of the image

  Ø  the cell size (the area represented by each pixel)

  Ø  This information is usually the same for each layer of an image file, although it could be different

  Ø  For example, the cell size of band 6 of Landsat TM data is different than the cell size of the other bands
• Rectification

  • Use methods based on statistical operations: “Ground Control Point rectification” (Star & Estes 1990).
• Rectification

  • Localization of visible points in the images are related to same points in reality (or on maps).
• Rectification

  • Establish relationship between the image coordinate system and the map coordinates
• Rectification

  • Together they form polynomials and their coefficients calculated by regression (Star et al 1990).
• Rectification

  • Error is given as RMS error (Root Mean Square) that denote

  difference between output location for a GCP and the real coordinates for the same point when the point is recalculated via a matrix of transformation.
• Rectification

  • Use interpolation to determine values for the new grid point. Rectification

  • Establish relationship between the image coordinate system and the map coordinates
• Rectification

  • Together they form polynomials and their coefficients calculated by regression (Star et al 1990).
• Rectification

  • Error is given as RMS error (Root Mean Square) that denote

  difference between output location for a GCP and the real coordinates for the same point when the point is recalculated via a matrix of transformation.
• Rectification

  • Use interpolation to determine values for the new grid point.
• GCPs are specific pixels in an image for which the output map coordinates (or other output coordinates) are known.
• GCPs consist of two X,Y pairs of coordinates:
• Source coordinates—usually data file coordinates in the image being rectified.
• Reference coordinates—the coordinates of the map or reference image to which the source image is being registered.
• The term map coordinates is sometimes used loosely to apply to reference coordinates and rectified coordinates. These coordinates are not limited to map coordinates.
• Depending upon the distortion in the imagery, the number of GCPs used, and their locations relative to one another, complex polynomial equations may be required to express the needed transformation
• The degree of complexity of the polynomial is expressed as the order of the polynomial (simply the highest exponent used in the polynomial)
• •         The order of transformation is the order of the polynomial used in the transformation

  •         Usually, 1st-order or 2nd-order transformations are used