Black & White and FCC Images


  • To describe how RS sensors obtain images
  • To describe how a color composite image is produced
  • To describe common color composite products generated with IRS data and discuss their the application to remote sensing

Black & White Images

All remote sensing sensors (MSS, TM, ETM, ETM+, LISS, etc) acquire images in black and white at precise wavelength intervals called bands (usually between 0.4 to 12.0 microns). These images, depending upon the radiometric resolution of the sensor, can have different number of gray levels (or DN values).  A 6-bit image, for instance, will have image data in 64 gray levels (26), while an 8-bit image will have 256 gray levels (28).  Image data acquired in any one band may therefore be displayed only in gray scale or black and white.  To obtain color images different bands are projected in different colors (red, green and blue) superposed to obtain color images.

Color Composites

In one single band from the IRS LISS II or LISS III sensor, the difference in energy levels between various land cover classifications may not be discernible. Since comparing the spectral characteristics of land features in multiple bands provides a better separation, or contrast between different land surfaces, IRS data from multiple bands can be combined to create a data product known as a composite image. IRS composite images are often called three-band composite images since they are created using the measured energy level in each of three spectral bands to control the amount of red, blue, and green in a color output image.

Mapping IRS data to an RGB display

Computers often use RGB (Red, Green, Blue) output to create color images. In an RGB display, all of the colors that make an image are made up of a combination of red, green, and blue at varying levels of intensity, each ranging from 0-255 (in an 8-bit image). Each unique color has its own combination of red, green, and blue levels. With all of the possible combinations of red, green, and blue values, this provides for a display system capable of using millions of different colors. In the diagram below, each unique color is displayed with its red, green, and blue values.

The way the IRS data are mapped into three colors in the output image depends on the information that one wishes to be highlighted in the images. The spectral characteristics of the target being observed and the type of information a researcher hopes to extract from the raw data determine which bands will be used in the composite and which color (red, green, or blue) will be assigned to each band. For example, in some applications, it may be desirable that land cover classes be associated with familiar colors (e.g., grass is green). In other cases contrasting colors are preferred to highlight objects of interest from the background.

Regardless of the combination of bands used, the mapping of IRS sensor data to the RGB color display is the same. Three bands are selected, each is assigned to one of the three primary RGB colors, and the value of each color level is mapped to the measured value of each pixel in the appropriate band. For example, to create a composite image that maps the measured values of bands 3, 2, and 1 to the colors red, green, and blue respectively, the color of each pixel would be calculated using the following logic:

  • The red value of the pixel would be set equal to the measured energy level of that pixel in band 3
  • The green value of the pixel would be set equal to the measured energy level of that pixel in band 2
  • The blue value of the pixel would be set equal to the measured energy level of that pixel in band 1

For example, assume one pixel location in the IRS scene has the following measured energy levels:

  • Measured energy level in band 3 = 18, which translates into a red value of 18
  • Measured energy level in band 2 = 18, which translates into a green value of 18
  • Measured energy level in band 1 = 133, which translates into a blue value of 133

This results is a RGB value of (18, 18, 133) for that pixel location in the color composite image, which is a deep blue color (this color can be seen in the image above). This logic is repeated for every pixel in the scene being processed, until an entire image is produced with the pixel values derived from a combination of each of the three bands.

IRS three-band composite images are usually named using the three bands used to create the image in order from red to green to blue. Thus, the above example would be called a "321 Composite" image, since it was derived from bands 3, 2, and 1 and they were mapped to red, green, and blue, respectively. The following section discusses some of the three-band composites that are commonly derived from IRS data.

True-Color Composite (321)

AMU Campus Example Image  of 321 Composite from LISS II data.  The bands have been linear contrast stretched.

True color composite images are created by combining the spectral bands that most closely resemble the range of vision of the human eye. A true-color composite uses the visible red (band 3), visible green (band 2), and visible blue (band 1) channels to create an image that is very close to what a person would expect to see in a photograph of the same scene. The band to color mapping for a 321 Composite are:

  •          Band 3 (Visible red) = red

  •          Band 2 (Visible green) = green

  •          Band 1 (Visible blue) = blue

True color images are based entirely on reflected solar radiation in the visible portion of the electromagnetic spectrum. Haze in the atmosphere, shadows, clouds, and scattering all affect the quality and usefulness of a true-color composite. True-color images, particularly of LISS sensor, are often low in contrast and hazy in appearance (see image above) since blue light is more easily scattered by the atmosphere.  Sensors on satellites like IKONOS and Blackbird handle the scattering of blue band exceptionally well and their true color composites are as good as photographs (actually better!).

A true color composite from IKONOS is shown below.

Gleebruk town, Northern Sumatra.  IKONOS True color composite

True-color composite images can be very useful, especially when studying coastal regions, since energy in the visible bands can penetrate water surfaces. Particles in the water, such as sediment or algae, will reflect visible light and can therefore be detected by the sensors. Using true-color composite imagery, we can observe and measure the amount of sediment flowing from rivers into larger bodies of water such as the Gleebruk coast (above) following storm events. We can also locate and measure large blooms of algae that threaten the water quality and fishery production in coastal waterways.

Near Infrared Composite (432) or Standard FCC

A Near Infrared composite eliminates the visible blue band and uses a Near Infrared (NIR) band to produce the image. The resulting composite does not resemble what the human eye will see (for example, vegetation is red instead of green); however it is very useful to researchers. The mapping of color to band is:

Band 4 (NIR) = red
Band 3 (Visible red) = green
Band 2 (Visible green) = blue

AMU Campus Example Image of 432 Composite from LISS II data.  The bands have been linear contrast stretched.

Vegetation has a very high albedo in the NIR band since chlorophyll (the pigment in leaves that give plants their green color) reflects energy at this wavelength. Thus, in a 432 NIR composite image, vegetation is vividly depicted as varying shades of red. Since different types of vegetation have different levels of chlorophyll in their leaves, each type of plant has its own shade of red. This makes a 432 composite very useful in determining the extent of vegetation and in classifying different vegetation types as seen from space.

Water, which absorbs nearly all of the NIR energy that reaches its surface, appears very dark, nearly black, in a 432 NIR composite image. Therefore this type of imagery would not be useful for studying underwater features.

Short-wave Infrared Composite (743 or 742)

A Short-wave Infrared composite contains at least

Parts of Pithoragarh Distt, Uttaranchal Example Image of 742 Composite.  Data Source ASTER (VNIR and SWIR).

 one band in the short-wave infrared (SWIR) portion of the electromagnetic spectrum. The other bands used can vary depending on the use of the composite data. Some examples of SWIR composite images would include the following bands mapped to RGB colors:

  • Band 7 (SWIR) = red
  • Band 4 (NIR) = green
  • Band 3 (Visible red) = blue


  • Band 7 (SWIR) = red
  • Band 4 (NIR) = green
  • Band 2 (Visible green) = blue

The albedo of surface materials in the SWIR portion of the spectrum is determined primarily by the moisture content of the surfaces being measured. Vegetation that is under stress (due to drought, pests, climate change, pollution, etc) will generally have less moisture content than healthy vegetation. Therefore, in a SWIR composite image, vegetation stress can be detected and appropriate measures can be taken to protect vegetation in stressed areas. SWIR band composites are also very useful in detecting soil types and soil disturbance since moisture is an important characteristic of soil structure.


Three Band Color Composite Imagery,  Accessed July 12, 2006


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