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Environmental Remote Sensing GEOG 2021

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Greyscale Display. Put same information on R,G,B: August 1995. August ... Colour composites, greyscale Display, density slicing, pseudocoluor. Image arithmetic ... – PowerPoint PPT presentation

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Title: Environmental Remote Sensing GEOG 2021


1
Environmental Remote Sensing GEOG 2021
  • Lecture 2
  • Image display and enhancement

2
Image Display and Enhancement
  • Purpose
  • visual enhancement to aid interpretation
  • enhancement for improvement of information
    extraction techniques

3
Image Display
  • The quality of image display depends on the
    quality of the display device used
  • and the way it is set up / used
  • computer screen - RGB colour guns
  • e.g. 24 bit screen (16777216)
  • 8 bits/colour (28)
  • or address differently

4
Colour Composites
  • Real Colour composite
  • red band on red
  • green band on green
  • blue band on blue

Swanley, Landsat TM 1988
5
Colour Composites
  • Real Colour composite
  • red band on red

6
Colour Composites
  • Real Colour composite
  • red band on red
  • green band on green

7
Colour Composites
  • Real Colour composite
  • red band on red
  • green band on green
  • blue band on blue

approximation to real colour...
8
Colour Composites
  • False Colour composite
  • NIR band on red
  • red band on green
  • green band on blue

9
Colour Composites
  • False Colour composite
  • NIR band on red
  • red band on green
  • green band on blue

10
Colour Composites
  • False Colour composite
  • many channel data, much not comparable to RGB
    (visible)
  • e.g. Multi-polarisation SAR
  • HH Horizontal transmitted polarization and
    Horizontal received polarization
  • VV Vertical transmitted polarization and
    Vertical received polarization
  • HV Horizontal transmitted polarization and
    Vertical received polarization

11
Colour Composites
  • False Colour composite
  • many channel data, much not comparable to RGB
    (visible)
  • e.g. Multi-temporal data
  • AVHRR MVC 1995
  • April
  • August
  • September

12
Colour Composites
  • False Colour composite
  • many channel data, much not comparable to RGB
    (visible)
  • e.g. MISR -Multi-angular data (August 2000)

0o 45o -45o
RCC
Northeast Botswana
13
Greyscale Display
  • Put same information on R,G,B

August 1995 August 1995 August 1995
14
Density Slicing
15
Density Slicing
16
Density Slicing
  • Dont always want to use full dynamic range of
    display
  • Density slicing
  • a crude form of classification

17
Density Slicing
  • Or use single cutoff
  • Thresholding

18
Density Slicing
  • Or use single cutoff with grey level after that
    point
  • Semi-Thresholding

19
Pseudocolour
  • use colour to enhance features in a single band
  • each DN assigned a different 'colour' in the
    image display

20
Pseudocolour
  • Or combine with density slicing / thresholding

21
Image Arithmetic
  • Combine multiple channels of information to
    enhance features
  • e.g. NDVI
  • (NIR-R)/(NIRR)

22
Image Arithmetic
  • Combine multiple channels of information to
    enhance features
  • e.g. NDVI
  • (NIR-R)/(NIRR)

23
Image Arithmetic
  • Common operators Ratio
  • Landsat TM 1992
  • Southern Vietnam
  • green band
  • what is the shading?

24
Image Arithmetic
  • Common operators Ratio

topographic effects visible in all bands FCC
25
Image Arithmetic
  • Common operators Ratio (cha/chb)
  • apply band ratio
  • NIR/red
  • what effect has it had?

26
Image Arithmetic
  • Common operators Ratio (cha/chb)
  • Reduces topographic effects
  • Enhance/reduce spectral features
  • e.g. ratio vegetation indices (SAVI, NDVI)

27
Image Arithmetic
  • Common operators Subtraction

An active burn near the Okavango Delta,
Botswana NOAA-11 AVHRR LAC data (1.1km pixels)
September 1989. Red indicates the positions
of active fires NDVI provides poor
burned/unburned discrimination Smoke plumes
gt500km long
  • examine CHANGE e.g. in land cover

28
Top left AVHRR Ch3 day 235 Top Right AVHRR
Ch3 day 236 Bottom difference pseudocolur
scale black - none blue - low red -
high Botswana (approximately 300 300km)
29
Image Arithmetic
  • Common operators Addition
  • Reduce noise (increase SNR)
  • averaging, smoothing ...
  • Normalisation (as in NDVI)



30
Image Arithmetic
  • Common operators Multiplication
  • rarely used per se logical operations?
  • land/sea mask

31
Histogram Manipluation
  • WHAT IS A HISTOGRAM?

32
Histogram Manipluation
  • WHAT IS A HISTOGRAM?

33
Histogram Manipluation
  • WHAT IS A HISTOGRAM?

Frequency of occurrence (of specific
DN)
34
Histogram Manipluation
  • Analysis of histogram
  • information on the dynamic range and distribution
    of DN
  • attempts at visual enhancement
  • also useful for analysis, e.g. when a multimodal
    distibution is observed

35
Histogram Manipluation
  • Analysis of histogram
  • information on the dynamic range and distribution
    of DN
  • attempts at visual enhancement
  • also useful for analysis, e.g. when a multimodal
    distibution is observed

36
Histogram Manipluation
Typical histogram manipulation algorithms Linear
Transformation

255
output
0
0
255
input
37
Histogram Manipluation
Typical histogram manipulation algorithms Linear
Transformation

255
output
0
0
255
input
38
Histogram Manipluation
Typical histogram manipulation algorithms Linear
Transformation
  • Can automatically scale between upper and lower
    limits
  • or apply manual limits
  • or apply piecewise operator

But automatic not always useful ...
39
Histogram Manipluation
Typical histogram manipulation algorithms Histogr
am Equalisation

Attempt is made to equalise the frequency
distribution across the full DN range
40
Histogram Manipluation
Typical histogram manipulation algorithms Histogr
am Equalisation

Attempt to split the histogram into equal areas
41
Histogram Manipluation
Typical histogram manipulation algorithms Histogr
am Equalisation

Resultant histogram uses DN range in proportion
to frequency of occurrence
42
Histogram Manipluation
Typical histogram manipulation algorithms Histogr
am Equalisation
  • Useful automatic operation, attempting to
    produce flat histogram
  • Doesnt suffer from tail problems of linear
    transformation
  • Like all these transforms, not always successful
  • Histogram Normalisation is similar idea
  • Attempts to produce normal distribution in
    output histogram
  • both useful when a distribution is very skewed
    or multimodal skewed

43
Histogram Manipluation
Typical histogram manipulation algorithms Gamma
Correction
  • Monitor output not linearly-related to voltage
    applied
  • Screen brightness, B, a power of voltage, V
  • B aV?
  • Hence use term gamma correction
  • 1???3 for most screens

44
Summary
  • Display
  • Colour composites, greyscale Display, density
    slicing, pseudocoluor
  • Image arithmetic
  • ??
  • Histogram Manipulation
  • properties, transformations

45
Summary
  • Followup
  • web material
  • http//www.geog.ucl.ac.uk/plewis/geog2021
  • Mather chapters
  • Follow up material on web and other RS texts
  • Learn to use Science Direct for Journals
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