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Remote sensing image correction. Introductory readings – remote sensing http://www.microimages.com/documentation/Tutorials/introrse.pdf. Preprocessing. Digital Image Processing of satellite images can be divided into: Pre-processing Enhancement and Transformations - PowerPoint PPT Presentation
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Remote sensing image correction
Introductory readings – remote sensing
http://www.microimages.com/documentation/Tutorials/introrse.pdf
Preprocessing
Digital Image Processing of satellite images can be divided into:
Pre-processing
Enhancement and Transformations
Classification and Feature extraction
Preprocessing consists of: radiometric correction and geometric correction
Preprocessing
Radiometric Correction: removal of sensor or atmospheric 'noise', to more accurately represent ground conditions - improve image‘fidelity’:
correct data loss
remove haze
enable mosaicking and comparison
Geometric correction: conversion of data to ground coordinates by removal of distortions from sensor geometry
enable mapping relative to data layers
enable mosaicking and comparison
Radiometric correction: modification of DNs
Errors
Radiometric correction
Radiometric correction is used to modify DN values to account for noise, i.e. contributions to the DN that are a result of…
a. the intervening atmosphere
b. the sun-sensor geometry
c. the sensor itself – errors and gaps
Radiometric correction
We may need to correct for the following reasons:
a. Variations within an image (speckle or striping)
b. between adjacent / overlapping images (for
mosaicing)
c. between bands (for some multispectral
techniques)
d. between image dates (temporal data) and
sensors
Errors: Sensor Failure & CalibrationSensor problems show as striping or missing lines of data: Missing data due to sensor failure results in a line of DN values - every 16th line for TM data .. As there are 16 sensors for each band, scanning 16 lines at a time (or 6th line for MSS).
MSS 6 line banding – raw scan
MSS 6 line banding - georectified
TM data – 16 line banding
Sample DNs – shaded DNs are higher
Landsat ETM+ scan line corrector (SLC) – failed May 31 2003http://landsat.usgs.gov/products_slc_off_data_information.php
SLC compensates for forward motion of the scanner during scan
Atmospheric Interference: cloudsclouds affect all visible and IR bands, hiding features twice: once with the cloud, once with its shadow. We CANNOT eliminate clouds, although we might be able to assemble cloud-free parts of several overlapping scenes (if illumination is similar), and correct for cloud shadows (advanced).
[Only in the microwave, can energy penetrate through clouds].
Geometric CorrectionCorrected image scene orientation ‘map’ Uncorrected data ‘path’
Pixels and rows
Group discussion• Why is rectification needed for remote sensing images?
Why is rectification neededRaw remote sensing data contain distortions preventing overlay with map layers, comparison between image scenes, and with no geographic coordinates
To provide georeferencing
To compare/overlay multiple images
To merge with map layers
To mosaic images
e.g. google maps / google earth
*** Much imagery now comes already rectified … YEAH !!
Image distortionsIn air photos, errors include:
topographic and radial displacement;
airplane tip, tilt and swing (roll, pitch and yaw).
These are less in satellite data due to altitude and stability.
The main source of geometric error in satellite data is satellite path orientation (non-polar)
Geocorrection
Rectification – assigning coordinates to (~6) known locations - GCPs
GCP = Ground Control Point
Resampling - resetting the pixels (rows and columns) to match the GCPs
RectificationData pixels must be related to ground locations, e.g. in UTM coordinates
Two main methods:
- Image to image (to a geocorrected image) .... to an uncorrected image would be 'registration' not rectification
-Image to vectors (to a digital file)....
(black arrows point to known locations- coordinates from vectors or images)
Ortho-rectification = this process (since ~2000) enables the use of a DEM to also take into account the topography
Resampling methods
http://www.geo-informatie.nl/courses/grs20306/course/Schedule/Geometric-correction-RS-new.pdf
New DN values are assigned in 3 ways
a.Nearest Neighbour Pixel in new grid gets the value of closest pixel from old grid – retains original DNs b. Bilinear Interpolation New pixel gets a value from the weighted average of 4 (2 x 2) nearest pixels; smoother but ‘synthetic’
c. Cubic Convolution (smoothest)New pixel DNs are computed from weighting 16 (4 x 4) surrounding DNs
Resampling
http://www.geo-informatie.nl/courses/grs20306/course/Schedule/Geometric-correction-RS-new.pdf
Good rectification is required for image registration – no ‘movement between images
Canadian Arctic mosaic
See also google maps, lrdw.ca/imap etc..
Northern Land Cover of
Canada – Circa 2000
http://ccrs.nrcan.gc.ca/optical/landcover2000_e.php
Striping from projecting SRTM data, from Lat/long to UTM; Chile
Now for something completely different – perfect registration needed….
100% Marilyn Monroe -> 100% Margaret Thatcher
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