1. Color on Remotely Sensed Imagery

2. Student Learning Outcome
Explain why RS data look the way they do on digital grayscale or color image displays.

3. The Explanation
The brightness values (BVs) of pixels in a remote sensing image vary across the image due to variations in the landscape represented by the image.
2009 NAIP Natural Color

4. The Explanation
The BV of any given pixel is determined by two factors, the radiance recorded for that pixel and the quantization level of the remotely sensed data.
BV (8-bit)
255 - white
127 - grey
0 - black
7-bit
(0 – 127)
Grayscale
8-bit
(0 –255)
9-bit
(0 –511)
12-bit
(0 –1,023)

5. The Explanation
Digital grayscale displays of remote sensing data show only one band of an image and BVs for that band are represented in shades of gray: the higher the BV, the lighter the shade of gray.
Landsat TM Band 1 (Blue-Green)
Landsat TM Band 2 (Green)
Landsat TM Band 3 (Red)
Landsat TM Band 4 (Near Infrared)
Grayscale
Low BVs
High BVs

6. The Explanation
Digital color displays of remote sensing data show up to three bands of an image using the RGB color model.

7. The Explanation RGB Color Model Based on additive color theory
Applies to illuminant mode
Light emitted from computer monitor, etc.
Additive primary colors:
Red, green blue
Yield new colors when combined
Red + Green = Yellow
Red + Blue = Magenta
Green + Blue = Cyan
Red + Green + Blue = White
Absence of color = Black

8. The Explanation RGB Color Model Visualized using RGB color cube
Black (0, 0, 0) at origin
Three axes (R, G, B) radiating outward from origin at 90°
Each primary specified in steps of 256 increments ranging from 0 to 255
White (255, 255, 255) at maximum of all three primaries
Blue
Black *
Green
Red

9. The Explanation RGB Color Model
Quantified using RGB color coordinate system

10. The Explanation Colors are classified using three descriptors Hue
Name of color: red, green, blue, ...
Saturation / chroma / intensity / purity
Brightness or dullness of a color
Value / tone
Lightness or darkness of a color

11. The Explanation
Digital color displays of remote sensing data, aka color composites, are generated by placing one image band in the Red color gun, another in the Green color gun, and yet another one in the Blue color gun, and by ultimately combining the three bands in a single image using additive color theory.

12. The Explanation
In digital color displays of remote sensing data, BVs in each band are represented in varying saturation levels of R, G, and B: the higher the BV, the higher the saturation level.
Low BVs
High BVs
Red Color Gun
RGB = 255, 255, 255
RGB = 255, 130, 130
RGB = 255, 0, 0
Green Color Gun
RGB = 255, 255, 255
RGB = 130, 255, 130
RGB = 0, 255, 0
Blue Color Gun
RGB = 255, 255, 255
RGB = 130, 130, 255
RGB = 0, 0, 255

13. The Explanation
So, in digital color displays, pixels with low BVs in all bands are black; pixels with high BVs in all bands are white; and pixels with intermediate BVs are red, green, blue, or a color resulting from the addition of these three primary colors, depending on the specific BVs in the different bands.

14. The Explanation Natural color (RGB = R, G, B)
Color-infrared (RGB = NIR, R, G)

15. The Explanation
Because there is often no one-to-one relationship between the BVs and the coordinate system used to represent the BVs (e.g., BVs may range from 0 to 100% but color values may range from 0 to 255), look-up tables (LUTs) – separate blocks of computer memory – are needed. LUTs basically specify the relationship between the original BVs and the gray level / color intensity of pixels in the output image. Color images have a set of three LUTs for each of the three R, G, and B guns. Grayscale images have identical LUTs for the three R, G, and B guns.

16. The Explanation Color LUTs: 8-Bit
Example 1: Black-and-white display of Landsat TM band 4 of Charleston, SC.
Example 2: Color density slice of Landsat TM band 5 of Charleston, SC, using the logic summarized on the following table.

17. The Explanation Color LUTs: 8-Bit Color Class Interval Visual Color
Color LuT Values R, G, B BV
Low High 1
Cyan
0, 255, 255
Shade of gray
17, 17, 17
18, 18, 18
19, 19, 19 *
59, 59, 59 2
Red
255, 0, 0

18. The Explanation Color LUTs: 8-Bit
Black-and-white display of predawn TIR imagery of the Savannah River.
Color density slice of the Savanna River TIR imagery.

19. The Explanation Color LUTs: 8-Bit Color Class Interval Visual Color
Color LuT Values
R, G, B
Temperature
Low High BV
1. Land
Gray
127,
2. River Ambient
Dark blue
0, 0, 120 C
Light blue
0, 0, 255
– 2.8 C
Green
0, 255, 0
– 5.0 C
Yellow
255, 255, 0
– 10.0 C
Orange
255, 50, 0
– 20 C
Red
255, 0 , 0
8. > 20 C
White
255, 255,255

20. The Explanation
Color LUTs: 24-Bit R G B

21. 4 3 2 1 NAIP Natural Color Orthophoto (RGB = 123)
Landsat TM False Color Image
(RGB = 432)
Landsat TM Natural Color Image
(RGB = 321)
Landsat TM Band 1 (Blue-Green)
Landsat TM Band 2 (Green)
Landsat TM Band 3 (Red)
Landsat TM Band 4 (Near Infrared)

22. AOI #1
Fallow Field
Crops
RGB = 4, 3, 2
Pecans
Stream
RGB = 3, 2, 1

23. Red
Band 4 +
Green
Band 3 =
RGB = 4, 3, 2 +
Blue
Band 2

24. Red
Band 3 +
Green
Band 2 =
RGB = 3, 2, 1 +
Blue
Band 1

25. AOI #2 RGB = 4, 3, 2 RGB = 3, 2, 1 Pond Rangeland 1 Rangeland 2
Exposed Soil
RGB = 3, 2, 1

26. Red
Band 4 +
Green
Band 3 =
RGB = 4, 3, 2 +
Blue
Band 2

27. Red
Band 3 +
Green
Band 2 =
RGB = 3, 2, 1 +
Blue
Band 1

28. AOI #3 RGB = 4, 3, 2 RGB = 3, 2, 1 Baseball Outfield Parking Lot
Baseball Infield
RGB = 4, 3, 2
Commercial Roof
RGB = 3, 2, 1

29. Red
Band 4 +
Green
Band 3 =
RGB = 4, 3, 2 +
Blue
Band 2

30. Red
Band 3 +
Green
Band 2 =
RGB = 3, 2, 1 +
Blue
Band 1

31. AOI #4 RGB = 4, 3, 2 RGB = 3, 2, 1 Residential New Grassy Field
Exposed Soil
Residential Old
RGB = 3, 2, 1

32. Red
Band 4 +
Green
Band 3 =
RGB = 4, 3, 2 +
Blue
Band 2

33. Red
Band 3 +
Green
Band 2 =
RGB = 3, 2, 1 +
Blue
Band 1

34. Mangrove Ecosystem,
Southern Florida
G, R, NIR G R
NIR