DIGITAL IMAGE PROCESSING

Introduction Geo-Information Science (GRS-10306)

Digital image processing - Topics

� Image representation (rescaling, colour composites)

� Image space - feature space

� Classification

Image Processing OptionsTape/DVD/CD: Screen:latent image → Visualization → picture 1

picture 2--------------

picture nOptions:e.g. spectral band selection filtering

displaying band composites band ratioingcontrast modification vegetation index computationhistogram equalization classificationgrey scale enhancement texture analysiscolour assignment segmentationdensity slicing geometric correctionprincipal componentstransformation

Contrast ModificationGrey scale enhancement(stretching):

Histogram

No stretch

Linear stretch

Histogram stretch

Image values

Image values

Image values

Display values

Display values

Display values

60

60

60

60

108

108

108

158

158

158

158

255

255

255

255

255

255

0

0

0

0

0

0 38

127

Linear stretchequal data intervals and unequal frequencies

0

5000

10000

15000

20000

25000

1 3 5 7 9 11 13 150 2 4 6 8 10 12 14

Num

ber

of p

ixel

s pe

r co

lour

cla

ss

Histogram equalizationunequal data intervals and approximately equal frequencies

0

2000

4000

6000

8000

10000

12000

14000N

umbe

r of

pix

els

per

colo

ur c

lass

1 3 5 7 9 11 13 150 2 4 6 8 10 12 14

Result: high frequent DN-values in the image are divided into small steps(intervals) at the display, so the result is a picture with more contrast.

Example of black-and-white image without stretching

Linear stretch

Histogram equalization

Colour Theory

� Additive colours (e.g. TV, PC, digital image processing):Blue + Green + Red = WhiteB + G = CyanB + R = MagentaG + R = Yellow

� Subtractive colours (e.g. colour films, AP, printing):Cyan = W - RMagenta = W - GYellow = W - B

Additive Colours

Subtractive Colours

Colour Composite ImagesNote: there is a difference between:

• spectral colours (related to visible EM wavelengths) → fixed• image processing colours (using monitor colour guns B, G, R) → variable

In image processing systems the assignment of spectral bands tothe colour guns is free !

E.g.: TM band: Colour gun:1 blue green2 green red3 red blue

The resulting pictures will look quite different, although the information presented is identical (same image).

Examples Colour Composites

TM band 1: blue

TM band 2: green "true colour”TM band 3: red

TM band 2: blueTM band 3: green "false colour”

TM band 4: red

SPOT band 1: blue

SPOT band 2: green "false colour”SPOT band 3: red

Example TM-image, band 3-2-1 (R,G,B)

Example TM-image, band 4-3-2 (R,G,B)

Example TM-image, band 2-3-4 (R,G,B)

Image Space - Feature Space

24 30 40 25 62135 26

9 77682833289628

44

10

39784

229

107

27857

30 54 157 54 6

12 19168

79

Scan directionF

light

dire

ctio

nD

igita

l num

ber

band

2

Digital number band 1

Image spacespatial patterns

Feature spacespectral patterns

Image Space - Feature Space

24 30 40 25 62135 26

9 77682833289628

44

10

39784

229

107

27857

30 54 157 54 6

12 19168

79

Scan directionF

light

dire

ctio

n

Digital number band 1

Dig

ital n

umbe

r ba

nd 2

A

B

CFeature spacespectral patterns

Image spacespatial patterns

Classification

( = ordering, discrimination, assigning labels)

• supervised: using ground truth, training areas

• unsupervised: using no field information

Steps in the classification process:

(1) choice of the decision rule(2) assigning class labels to all pixels of the image(3) evaluation of the classification result by analyzing

spatial patterns in the image space(4) if necessary, adjusting the classfication result

Minimum distance to means classification

1

Digital number band 4

water

urban

forest

crop

soil

heather

2

3

Dig

ital n

umbe

r ba

nd 3

Nearest neighbour classification

Digital number band 4

water

urban

forest

crop

soil

heather

3

2

1

Dig

ital n

umbe

r ba

nd 3

Maximum likelihood classification

Dig

ital n

umbe

r ba

nd 3

Digital number band 4

water

urban

forest

crop

soil

heather

1

2

3

Parallelepiped (box) classification

Digital number band 4

water

urban

forest

crop

soil

heather

2

1

3

Dig

ital n

umbe

r ba

nd 3

Classification “Noordoostpolder”