Involves the manipulation and interpretation of digital images with the aid of a computer.

1. Digital Image Processing • Involves the manipulation and interpretation of digital images with the aid of a computer. • Includes: • Image preprocessing (rectification and restoration) • Image enhancement: for efficient visual interpretation • Image classification: thematic information extraction or pattern recognition) • Data merging and GIS integration • Hyper-spectral image analysis • Biophysical modeling • Image transmission and compression

2. Image preprocessing • Image preprocessing aims to correct distorted or degraded image data to create a more faithful representation of the original scene. Includes: • Rectification: Correct for geometric distortion in the raw image data. • Restoration: Calibrate the degraded data radiometrically.

3. Systematic Distortions in RS Data • Scan Skew: Caused by the forward motion of the platform during the time required for each mirror sweep. The ground swath is not normal to the ground track but is slightly skewed, producing cross-scan geometric distortion. • Mirror-Scan Velocity Variance: The mirror scanning rate is usually not constant across a given scan, producing along-scan geometric distortion. • Platform Velocity: If the speed of the platform changes, the ground track covered by successive mirror scans changes, producing along-track scale distortion. • Earth Rotation: Earth rotates as the sensor scans the terrain. This results in a shift of the ground swath being scanned, causing along-scan distortion.

4. Image Skew a) Landsat satellites 4, 5, and 7 are in a Sun-synchronous orbit with an angle of inclination of 98.2. The Earth rotates on its axis from west to east as imagery is collected. b) Pixels in three hypothetical scans (consisting of 16 lines each) of Landsat TM data. While the matrix (raster) may look correct, it actually contains systematic geometric distortion caused by the angular velocity of the satellite in its descending orbital path in conjunction with the surface velocity of the Earth as it rotates on its axis while collecting a frame of imagery. c) The result of adjusting (deskewing) the original Landsat TM data to the west to compensate for Earth rotation effects.

5. The diameter of the spot size on the ground (D; the nominal spatial resolution) is a function of the instantaneous-field-of-view (b) and the altitude above ground level (H) of the sensor system, i.e.

6. Non-Systematic Distortions in RS Data AltitudeVariance: If the sensor platform departs from its normal altitude or the terrain increases in elevation, this produces changes in scale Platform Attitude: One sensor system axis is usually maintained normal to Earth's surface. If the sensor departs from this attitude, geometric distortion results.

7. Geometric Distortions in RS Data • Pitch: Rotation of an aircraft about the horizontal axis normal to its longitudinal axis that causes a nose-up or nose-down attitude. • Roll: Rotation of an aircraft that causes a wing-up or wing-down attitude. • Yaw: Rotation of an aircraft about its vertical axis so that the longitudinal axis deviates left or right from the flight line. Effects of Pitch, Roll, and Yaw.

8. a) Geometric modification in imagery may be introduced by changes in the aircraft or satellite platform altitude above ground level (AGL) at the time of data collection. Increasing altitude results in smaller-scale imagery while decreasing altitude results in larger-scale imagery. b) Geometric modification may also be introduced by aircraft or spacecraft changes in attitude, including roll, pitch, and yaw. An aircraft flies in the x-direction. Roll occurs when the aircraft or spacecraft fuselage maintains directional stability but the wings move up or down, i.e. they rotate about the x-axis angle (omega: w). Pitch occurs when the wings are stable but the fuselage nose or tail moves up or down, i.e., they rotate about the y-axis angle (phi: f). Yaw occurs when the wings remain parallel but the fuselage is forced by wind to be oriented some angle to the left or right of the intended line of flight, i.e., it rotates about the z-axis angle (kappa: k). Thus, the plane flies straight but all remote sensor data are displaced by k.

9. Rectification for RS Data • Rectification: An image pre-processing procedures that correct systematic, non-systematic distortions in an image using ephemeris data. • Ephemeris: Any tabular statement of satellite parameters recorded at regular intervals. RS Satellites and ground stations record and maintain ephemeris data (velocity, pitch, radiometric calibration, solar elevation, etc.) along with image data so that the image data can be geometrically corrected at the ground receiving station.

10. Rectification • The entire process of transforming image data pixels from one pixel-based grid system into a georeferenced grid system using a series of ground control points (GCP) in conjunction with resampling algorithms. • It is prerequisite for image registration with other GIS layers:

11. Image Registration • The process of making the pixels in one image conform spatially to the pixels in another image. • Registration is necessary to compare images collected from multi-source or multi-temporal data in a GIS.

12. Creating a GCP Network • Visually, find conspicuous locations such as a crossroad, building corner, or field boundary on the source image, and note its pixel coordinates. • Find that same point on the reference file, and note its georeferenced coordinates. • Build up a network of these points spread out over the source image.

13. Ground Control Points • Several alternatives to obtaining accurate ground control point (GCP) map coordinates for geo-rectification include: • hard-copy planimetric maps (e.g., U.S.G.S.7.5-minute 1:24,000-scale topographic maps); • digital planimetric maps (e.g., the U.S.G.S.digital 7.5-minute topographic map series) where GCP coordinates are extracted directly from the digital map on the screen; • digital orthophotoquads that are already geometrically rectified (e.g., U.S.G.S. digital orthophoto quarter quadrangles —DOQQ); • Global positioning system (GPS).

14. a) U.S. Geological Survey 7.5-minute 1:24,000-scale topographic map of Charleston, SC, with three ground control points identified (13, 14, and 16). The GCP map coordinates are measured in meters easting (x) and northing (y) in a Universal Transverse Mercator projection. b) Un-rectified Landsat TM band 4 image with the three ground control points identified. The image GCP coordinates are measured in rows and columns.

15. Geometric Rectification: How? • Two basic operations must be performed to geometrically rectify a remotely sensed image to a map coordinate system: • Spatial coordinate transformation • Pixel Re-sampling

16. Geometric Rectification: Spatial Coordinate Transformation • Using a Polynomial Transformation Algorithm of which there are three types. • 1st Order • 2nd Order • 3rd Order

17. First Order Spatial Coordinate Transformation for Rectification where xand y are positions in the output-rectified image x and y are corresponding positions in the original input image.

18. NASA ATLAS near-infrared image of Lake Murray, SC, obtained on October 7, 1997, at a spatial resolution of 2  2 m. The image was rectified using a second-order polynomial to adjust for the significant geometric distortion in the original dataset caused by the aircraft drifting off course during data collection.

19. Pixel Resampling • After the image has been shifted, the pixel in a new grid may not fit exactly with the pixel in the source grid. • It is therefore necessary to assign values to pixels in the new, georectified, grid. • We do this using pixel resampling algorithms. • There are three types: • Nearest Neighbor • Bilinear Interpolation • Cubic convolution

20. Nearest Neighbor Resampling • Uses the digital value from the pixel in the original image whose center is nearest to the new pixel location in the corrected image. • The simplest method and does not alter the original values. • Tends to result in a disjointed or blocky image appearance • But is the best method if further processing, or a classification based on spectral response is to be done.

21. Bilinear Interpolation Resampling • Takes a weighted average of four pixels in the original image with centers nearest to the new pixel location. • The averaging process alters the original pixel values and creates entirely new digital values in the output image. • This method may be undesirable if further processing and analysis is to be done.

22. Cubic Convolution Resampling • Calculate a distance weighted average of a block of sixteen pixels from the original image which surround the new output pixel location. • As with bilinear interpolation, this method results in completely new pixel values, and should be avoided if further processing is to be done. • However, both methods produce images which avoid the blocky appearance of the nearest neighbor method.

23. Image Mosaicing The process of piecing together georeferenced images to form an image of a larger area. Overlap

24. Mosaicking