Department of Geomatics Remote Sensing

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Department of Geomatics Remote Sensing

• IMAGE PROCESSING DIGITAL FILTERS
• and
• PRINCIPAL COMPONENTS ANALYSIS

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Department of Geomatics Remote Sensing

• IMAGE PROCESSING DIGITAL FILTERS

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Department of Geomatics Remote SensingDigital
Filters

• SPATIAL INFORMATION FREQUENCY
• The way in which brightness varies with distance

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Department of Geomatics Remote SensingDigital
Filters

• SPATIAL INFORMATION FREQUENCY
• Low frequency spatial information
• High frequency spatial information
• Median frequency spatial information

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Department of Geomatics Remote Sensing DIGITAL
FILTERS

• Low Pass (Averaging)
• High Pass
• Edge Detection
• Edge Enhancement
• Directional

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Department of Geomatics Remote Sensing Digital
Filters

• Low Pass
• Used in removing noise
• Used in agggregating areas for classification
• Used to map long wavelength, low amplitude trends.

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Department of Geomatics Remote Sensing Digital
Filters

• High Pass
• Used to sharpen blurred images
• Used to map high spatial frequency features
• Edge detection
• Edge enhanced

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Department of Geomatics Remote Sensing Digital
Filters

• Directional
• Used to map high spatial frequency features at a
  particular orientation.
• Provide illumination across an image
  (interpretation aid)
• Enhances structures orthogonal to the specified
  direction.

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Department of Geomatics Remote Sensing

• IMAGE PROCESSING PRINCIPAL COMPONENTS ANALYSIS

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• PRINCIPAL COMPONENTS ANALYSIS
• Plotted in spectral space, all image data tend
  to be highly correlated.

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• PRINCIPAL COMPONENTS ANALYSIS
• Principle components analysis plots the
  directions of maximum variability in a data set

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• PRINCIPAL COMPONENTS ANALYSIS
• These directions are then used as new image axis.

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• PRINCIPAL COMPONENTS ANALYSIS
• De-correlates the image data.
• Produces an image of maximum variability.
• Good for detecting subtle spectral changes.

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