Image Pre-ProcessingImage Pre-Processing

Continuation…Continuation…

Spectral EnhancementSpectral EnhancementBrightness – Greenness – WetnessBrightness – Greenness – Wetness

BGWBGW

Image Pre-ProcessingImage Pre-Processing

Continuation…Continuation…

Spectral EnhancementSpectral EnhancementBrightness – Greenness – WetnessBrightness – Greenness – Wetness

BGWBGW

Image Pre-ProcessingImage Pre-ProcessingImage Pre-ProcessingImage Pre-Processing

• Radiometric Enhancement:Radiometric Enhancement:• Image RestorationImage Restoration• Atmospheric CorrectionAtmospheric Correction• Contrast EnhancementContrast Enhancement• Solar Angle AdjustmentSolar Angle Adjustment• Conv. to Exo-Atmos. ReflectanceConv. to Exo-Atmos. Reflectance

• Spectral Enhancement:Spectral Enhancement:• Spectral IndicesSpectral Indices• PCA, IHS, Color Transforms PCA, IHS, Color Transforms • T-Cap, BGWT-Cap, BGW

• Radiometric Enhancement:Radiometric Enhancement:• Image RestorationImage Restoration• Atmospheric CorrectionAtmospheric Correction• Contrast EnhancementContrast Enhancement• Solar Angle AdjustmentSolar Angle Adjustment• Conv. to Exo-Atmos. ReflectanceConv. to Exo-Atmos. Reflectance

• Spectral Enhancement:Spectral Enhancement:• Spectral IndicesSpectral Indices• PCA, IHS, Color Transforms PCA, IHS, Color Transforms • T-Cap, BGWT-Cap, BGW

Consists of processes aimed at the geometric and radiometric Consists of processes aimed at the geometric and radiometric correction, enhancement or standardization of imagery to correction, enhancement or standardization of imagery to improve our ability to interpret qualitatively and improve our ability to interpret qualitatively and quantitatively image components.quantitatively image components.

Consists of processes aimed at the geometric and radiometric Consists of processes aimed at the geometric and radiometric correction, enhancement or standardization of imagery to correction, enhancement or standardization of imagery to improve our ability to interpret qualitatively and improve our ability to interpret qualitatively and quantitatively image components.quantitatively image components.

• Spatial Enhancement:Spatial Enhancement:• Focal AnalysisFocal Analysis• Edge-DetectionEdge-Detection• High/Low Pass FiltersHigh/Low Pass Filters• Resolution MergesResolution Merges• Statistical FilteringStatistical Filtering• Adaptive FilteringAdaptive Filtering• Texture FiltersTexture Filters

• Geometric CorrectionGeometric Correction• Polynomial TransformationPolynomial Transformation• Ground Control PointsGround Control Points• ReprojectionsReprojections

• Spatial Enhancement:Spatial Enhancement:• Focal AnalysisFocal Analysis• Edge-DetectionEdge-Detection• High/Low Pass FiltersHigh/Low Pass Filters• Resolution MergesResolution Merges• Statistical FilteringStatistical Filtering• Adaptive FilteringAdaptive Filtering• Texture FiltersTexture Filters

• Geometric CorrectionGeometric Correction• Polynomial TransformationPolynomial Transformation• Ground Control PointsGround Control Points• ReprojectionsReprojections

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

The Brightness, Greenness, Wetness transform was first developed for use with the Landsat MSS system and called the “Tasseled Cap” transformation. The transform is based on a set of constants applied to the image in the form of a linear algebraic formula.

The transform developed for the MSS consisted of coefficients that extracted brightness and greenness. This was due to the spectral resolution of the MSS that focused primarily in the visible and near infrared.

The Brightness, Greenness, Wetness transform was first developed for use with the Landsat MSS system and called the “Tasseled Cap” transformation. The transform is based on a set of constants applied to the image in the form of a linear algebraic formula.

The transform developed for the MSS consisted of coefficients that extracted brightness and greenness. This was due to the spectral resolution of the MSS that focused primarily in the visible and near infrared.

B = 0.332MSS1 + 0.603MSS2 + 0.675MSS3 + 0.262MSS4

G = -0.283MSS1 – 0.660MSS2 + 0.577MSS3 + 0.388MSS4

B = 0.332MSS1 + 0.603MSS2 + 0.675MSS3 + 0.262MSS4

G = -0.283MSS1 – 0.660MSS2 + 0.577MSS3 + 0.388MSS4

Brightness – Greenness - WetnessBrightness – Greenness - WetnessFollowing the launch of Landsat 4 and the inclusion of the Thematic Mapper, these coefficients were recalculated to take advantage of the increased spectral resolution of the TM. This allowed for the extraction of an additional component called wetness due to the inclusion of the MIR channels that are sensitive to moisture absorption.

B = 0.2909TM1 + 0.2493TM2 + 0.4806TM3 + 0.5568TM4 + 0.4438TM5 +0.1706TM7

G = -0.2728TM1 – 0.2174TM2 - 0.55508TM3 + 0.7221TM4 + 0.0733TM5 – 0.1648TM7

W = 0.1446TM1 + 0.1761TM2 + 0.3322TM3 + 0.3396TM4 -0.6210TM5 – 0.4186TM7

B = 0.2909TM1 + 0.2493TM2 + 0.4806TM3 + 0.5568TM4 + 0.4438TM5 +0.1706TM7

G = -0.2728TM1 – 0.2174TM2 - 0.55508TM3 + 0.7221TM4 + 0.0733TM5 – 0.1648TM7

W = 0.1446TM1 + 0.1761TM2 + 0.3322TM3 + 0.3396TM4 -0.6210TM5 – 0.4186TM7

Brightness Brightness defined in the direction of soil reflectance variation. Obtained from a weighted sum of all bands. i.e. urbanized and bare soil areas are evident in this image.

Greenness Greenness defined in the direction of vegetation reflectance variation. Obtained from the contrast of the visible bands (high absorption) with the infrared bands (high reflectance). i.e. the greater the biomass, the brighter the pixel value in this image.

Wetness Wetness information concerning the moisture status of the environment (soil & plant moisture). Obtained from the contrast of the sum of visible and near-infrared with the sum of longer-infrared bands. i.e. water bodies are very bright – greater the moisture content = brighter response.

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

Brightness

Greenness

Concrete Bare soil

Healthy – densevegetation

Water

Clear Turbid

BrightnessThird

Water

Clear Turbid

Wet soil

Dry soil

Location for different land cover classes in theB-G spectral space

Jensen - 2005

Concrete, Bare soil

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

What happens when atmospheric correction is not feasible?

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

Landsat TM Band 3

Lan

dsat

TM

Ban

d 4

Gre

enne

ssBrightness

These feature space plots depict the relationship between the red and NIR reflectance as recorded by the Thematic Mapper and the relationship between Brightness and Greenness from the same data set.

These feature space plots depict the relationship between the red and NIR reflectance as recorded by the Thematic Mapper and the relationship between Brightness and Greenness from the same data set.

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

BrightnessBrightness GreenessGreeness

WetnessWetness

Brightness – Greenness - WetnessBrightness – Greenness - Wetness

Brightness – Greenness - WetnessBrightness – Greenness - WetnessApplications: Example

Brightness – Greenness - WetnessBrightness – Greenness - WetnessApplications: Example

Brightness – Greenness - WetnessBrightness – Greenness - WetnessApplications: Example