Remote Sensing Image Rectification and Restoration

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Remote Sensing Image Rectification and
Restoration
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Image Rectification and Restoration

• Geometric correction
• Radiometric correction
• Geometric restoration

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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

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Skew Correction
Coordinate transfer Pixel value resampling
http//rst.gsfc.nasa.gov/Intro/Part2_15.html
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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

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Finding UTM coordinates on a map
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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)
• v(dx)2 (dy)2
• Calculate RMSE for all control points

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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

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Re-sampling Methods

• Nearest neighbor resampling
• Bilinear interpolation
• Cubic convolution resampling

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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

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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

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Cubic Convolution Resampling

• Uses DN values of the closest 16 pixels,
  adjusted by distance
• Advantage
• smooth output image
• Disadvantage
• alters the original DN values

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When to Rectify

• Rectify before image classification
• Rectify after image classification

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2. Radiometric Corrections

• Radiometric responses differ by
• dates
• sensor types
• images
• Causes
• - Illumination
• - Atmospheric conditions
• - View angle or geometry
• - Instrument response

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Radiometric Corrections

• Sun elevation correction
• Atmospheric correction
• Conversion to absolute radiance

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Sun Elevation Correction

• DN
• --------------------------------
• Sin (Sun elevation angle)
• Assuming the terrain is flat

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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

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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

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3. Geometric Restoration

• Stripping
• Line-drop
• Bit errors

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Striping

• Malfunction of a detector
• Use gray scale adjustment to correct the strips

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Line Drop

• using average of the above and below lines to
  fill the dropped line

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Bit Error

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

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Readings

• Chapter 7

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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

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Atmospheric Correction

• rET
• Ltot --------- Lp
• p
• r - reflection of target
• E - irradiance on the target
• T - transmission of atmosphere
• Lp - scattered path radiation