1. Remote Sensing Image Rectification and Restoration

2. Image Rectification and Restoration
Geometric correction
Radiometric correction
Geometric restoration

3. 1. Geometric Correction For raw image rectification
For multi-date images registration
For multi-resolution images or data layers registration
Systematic distortion vs. random distortion

4. Skew Correction Coordinate transfer Pixel value resampling

6. Ground Control Points (GCP)
Features with known locations on a map (X,Y coordinates). These are the “ground control points”
The same features can be accurately located on the images as well (column, row numbers)
The features must be well distributed on the map and the image
Highway intersections are commonly used ground control points

7. Finding UTM coordinates on a map

8. Coordinate Transform
Coordinate transform equations relate geometrically correct map coordinates to the distorted image coordinates
x = a0 + a1X + a2Y
y = b0 + b1X + b2Y
x,y: column, row number
X,Y: coordinates
Root Mean Square Error (RMSE)
= √(dx)2 + (dy)2
Calculate RMSE for all control points

9. Resampling
The purpose is to assign pixel values to the empty pixels in the rectified matrix output
Superimpose the rectified output matrix to the distorted image
The digital number (DN) of a pixel in the output matrix is assigned based on the DN of its surrounding pixels in the distorted image

10. Re-sampling Methods Nearest neighbor resampling Bilinear interpolation
Cubic convolution resampling

11. Nearest Neighbor Resampling
The DN of a pixel in the output matrix is assigned as the DN of the closest pixel in the distorted image
Advantages
simple computation
maintain the original values
Disadvantage
spatial offset up to 1/2 pixel

13. Bi-linear Interpolation
Distance-weighted average of DN values of the closest 4 pixels
Advantage
output image is smoother than the nearest neighbor method
Disadvantage
alters the original DN values

14. Cubic Convolution Resampling
Uses DN values of the closest 16 pixels, adjusted by distance
Advantage
smooth output image
Disadvantage
alters the original DN values

16. When to Rectify Rectify before image classification
Rectify after image classification

17. 2. Radiometric Corrections
Radiometric responses differ by
dates
sensor types
images
Causes:
- Illumination
- Atmospheric conditions
- View angle or geometry
- Instrument response

18. Radiometric Corrections
Sun elevation correction
Atmospheric correction
Conversion to absolute radiance

19. Sun Elevation CorrectionDN
Sin (Sun elevation angle)
Assuming the terrain is flat

20. Spring / Fall
Satellite
Summer
Winter
Zenith
Equator
Tangent plane
Solar Elevation Angles

21. Atmospheric Correction
Haze compensation
The DN value of an object (e.g., a deep clear water body) with 0 reflectance = Lp
Subtract the DN from the entire band

22. Absolute Irradiance
Conversion of DN values to absolute radiance values
It is necessary when compare different sensors, or relate ground measurements to image data
L = (Lmax- Lmin)/255 * DN + Lmin

23. 3. Geometric Restoration
Stripping
Line-drop
Bit errors

24. Striping Malfunction of a detector
Use gray scale adjustment to correct the strips

25. Line Drop
using average of the above and below lines to fill the dropped line

26. Bit Error Salt and pepper effect due to random error
Use 3x3 or 5x5 moving window average to remove the noise

27. Readings
Chapter 7

28. Earth-Sun Distance Correction
E0 Cosq0
E = d2
Irradiance is inversely related to the square of the earth-sun distance
E - normalized solar irradiance
E0 - solar irradiance at the mean Earth-sun distance
q0 - sun angle from the zenith
d - Earth-sun distance

29. Atmospheric Correction
rET
Ltot = Lp p
r - reflection of target
E - irradiance on the target
T - transmission of atmosphere
Lp - scattered path radiation