MULTI-SPECTRAL IMAGE GALLERY

 

Use Scroll Bar at Right to View Entire List of Image Samples

 
  Multi-spectral Image FAQ

 

What is a multi-spectral image?

 

A multi-spectral image is one that represents a scene in terms of specific bands of electromagnetic radiation that often include frequencies outside of the visible spectrum.  Many invisible bands of radiation, especially in the near-infrared (NIR), provide information that is valuable in the study of vegetation.   Multi-spectral images may be viewed as single monochromatic (gray-scale) images of one band at a time or in combinations of three bands in a common composite image.  In color photography, color composite images are made up of varying levels of closely-spaced true colors (red, green and blue) that faithfully communicate the visible colors in a scene to the red, green and blue color receptors in our eyes.  When NIR frequencies are shown in multi-spectral color composite images, the images are described as either "Color-Infra-Red (CIF)" or "false color" images.  Either of these terms could be applied to the image shown below.  A false-color image  is a more generic term that refers to any image that depicts scenery in colors that differ from those that a photograph or "true-color" image would show.

 

 

EXAMPLE OF FALSE COLOR MULTI-SPECTRAL IMAGE

Why do "false-color" multi-spectral  images often appear rosy in color? 

 

Systems in Tetracam's ADC family of multi-spectral cameras capture green (520600 nm), red (630690 nm) and NIR (760900 nm) bands in high-resolution still images.  In "false-color" images like the one above, invisible NIR in the scene is converted to red in the image.  Green in the scene is converted to blue in the image.  And red in the scene is converted to green in the image.  Since healthy vegetation strongly reflects near-infrared and also green radiation, everywhere that healthy vegetation is present in the scene appears magenta (red + blue) in the image.  Buildings, roads and other areas where no vegetation is present, reflect a full spectrum  of visible and NIR solar radiation but absorb much of this as well so they appear in shades of gray (R+G+B) in the image.  The rosy colored areas in a multi-spectral image indicate the presence of healthy vegetation.  The higher the level of NIR, the more photo-synthetically active the plant and the redder the plant appears in the multi-spectral image.


 

What is an NDVI image? 

 

When plants are stressed, the level of the NIR radiation that they reflect immediately drops. So, multi-spectral false color images provide very good early warning signs of crop problems.  The small color variations that signal the onset of trouble, however, are difficult to spot in a false color image.  A Normalized Difference Vegetation Index (NDVI) provides a graphical way to quantify small changes in multi-spectral image color relationships.  These images consist of pixels with values determined by the formula, (NIR -RED)/(NIR +RED).  This formula compares the amount of reflected NIR radiation with the amount of reflected red radiation.   Where healthy vegetation dominates the scene, the NDVI formula approaches (NIR/NIR) or +1 in value.  Where there is an absence of NIR-reflecting vegetation, the NDVI value approaches (-RED/+RED) or -1 in value.  

 

EXAMPLE OF NDVI IMAGE

 

PixelWrench2, the software that comes with all Tetracam cameras, lets users derive NDVI and other graphical vegetation indices from false color images.  It allows users to provide a color code for small changes in the values between +1 and -1.  It shows the colors in a legend to the right of the image.  And, in the same legend, it shows the percentage of each NDVI value that is present in the image.  So, if there is a change in NDVI values between successive imaging sessions, changes in the legend make the changing NDVI values easy to recognize and the color code makes the location of the change in the scene easy to locate.  Growers can treat the individual failing plant rather than treat the entire field, and they can begin to treat that plant long before it gives any visible indication that anything is wrong.  


Are multi-spectrum imaging systems limited to just monitoring green, red, and near-infrared bands?

 

Since the 1970's, broad portions of the green, red, and near-infrared sections of the electromagnetic spectrum have been monitored by Landsat satellites so there are a lot of historic images that show different plant species in different areas of the world displayed in terms of these bands.  Tetracam's ADC family of cameras monitors red, green and near-infrared using the same filter values used in Landsat satellites.  This allows systems in the ADC family to extract vegetation indices such as NDVI comparable to those derived from Landsat satellite images but there are many other bands of frequencies that identify specific information about the imaged scene (see a discussion on some of the most commonly-used bands here). 

 

Tetracam's Micro-MCA systems may be configured with combinations of four, six or twelve narrow-band optical filters of the user's choice that are within the sensor's range of slightly under 450 nm to slightly over 1000 nm.  Each selected filter produces a monochrome image that shows the amount of radiation that the filter passes at each pixel location in the image.  The brighter the pixel, the more radiation passed at the filtered frequency.  As with ADC images, Micro-MCA images may be stored in three native Tetracam file formats; 8-bit RAW, 10-bit RAW or 10-bit DCM.  It is necessary to use PixelWrench2 to view Tetracam native file formats but this same software can convert native file formats into standard formats such as Bit-Map (BMP), Tagged Image File Format (TIFF),  Windows Meta-File (WMF), Portable Network Graphic (PNG) or a Joint Photographic Expert Group image (JPEG) such as the one shown below. 

 

 

 

EXAMPLE OF A MONOCHROME IMAGE CAPTURED BY A MINI-MCA6 (six of these, one for each band, were captured at the same time and stored on six different flash memory cards in a Mini-MCA6).  PixelWrench2 was used to convert one of the system's RAW images into jpeg format for display here. In order to view the six original images of this scene in their native format, download PixelWrench2 from this link then download the files by clicking on each link below.  View the downloaded images by loading each using PixelWrench2.  Each Micro-MCA system is shipped with an MCA Global Alignment File.  This identifies information about the filters shipped with each system.  The Global Alignment File relevant to the images shown below follows the file names.

 

TTC00083

TTC10083

TTC20083

TTC30083

TTC40083

TTC50083

MCA Global Alignment File

 

PixelWrench2 allows the Micro-MCA's multiple image files to be viewed one by one as monochrome images or as composite color images or to be arranged as perfectly-registered multi-page images.  Users may scroll over each pixel in a multi-page image to view a histogram showing the distribution and amplitude of the frequencies that are present at that location in the scene.  These histograms provide an excellent tool for identifying unique spectral signatures of compounds, plant species or specific plant conditions that are present at each location. 


 

How are multi-spectral images affected by changes in ambient lighting conditions and changes in the exposure settings of the camera itself?

 

Tetracam systems are shipped with factory-set calibration values that relate the gain of each filtered channel to one another given the transmittance of each filter and the standard values of the sun's irradiance through the Earth's atmosphere at the monitored frequencies. If ambient conditions arise that change these relationships, image inaccuracies may be corrected using a teflon calibration tag shipped with each system.  Capturing an image of this tag under the prevailing conditions prior to each imaging session enables PixelWrench2 to correct the relative gain of each channel for local variations that would otherwise throw off image accuracy. 

 

The individual exposure settings of the master camera in a Micro-MCA array may be set by users to deliver the best image results under the available lighting conditions.  If a user is unsure of which exposure setting to use then the system may be placed into auto-exposure mode.  In this, the system automatically calculates and adjusts exposure settings to match the scene's mid-tone to the mid-tone of the master camera image.  Operating the Micro-MCA in auto-exposure mode evenly brightens the image for best viewing of detail without changing the relative brightness of individual bands with respect to one another.  Since the system's auto-exposure algorithm does not change,  it is consistently applied from one image to the next.  In most applications this enables users to accurately identify, measure or assess the conditions that they are investigating.  Where absolute reflectance values are required, users may purchase an incident light sensor for use with their Micro-MCA.

 


The Incident Light Sensor returns absolute reflectance values by measuring the amount of incident radiation that is down welling from the sun at each of the monitored wavelengths and the portion of that incident light that is reflected back to the camera at every pixel location in the image.  Images that represent absolute reflectance values typically appear darker than those that are optimized to display best overall image exposure (see sample images above).   Check out Tetracam's Incident Light Sensor for more information about this Micro-MCA accessory.

 

 

 
 

Sample Images from Aurea Imaging

 

 

 

Frost Damage Mosaic  (Violet areas are healthy trees.  Cyan areas are dead trees caused by frost damage)

 

 

 

Two mosaics of first year lemon trees (expressed in NDVI values)

 

 

Three  pictures of 150 ha wheat field. The left-most  is a composite image made using 810nm-740nm-690nm filters.  The center image shows Biomass based on NDVI.  The right-most image shows nitrogen content based on TCARI/OSAVI index, an advanced index using 550nm-660nm-740nm and 810nm

 

 

Click Here for Aurea Presentation

 


Sample Images from Geo-Konzept

 

 

 

              Mini-MCA Image at 750 nm of Sugar Beet Field in Germany (with GPS metadata)

 

Click Here  (231 MB Zipped Image File)

 

 

 


 

Sample Images from Grupo Acre

 

 

 

              Multi-spectral Image of Recopolis (Roman Ruins in Spain)

 

Click Here  (168 MB Zipped Image File)

 

 


 

Sample Images from IDETEC

 

 

 

 

Chilean Field

Mosaicking

Olivos NDVI


  Sample Mission Photos from Robota

 

 

 

 

Triton Mission

Zipped Images (65 Meg)

 


 

Sample RAW Images Taken from Hawkeye Parafoil 

Download File by Clicking on Link Below

View Using PixelWrench2

TTC03557

TTC03687

TTC03723

 

 


 

 

Sample DCM Images

Download File by Clicking on Link Below

View Using PixelWrench2

 

TTC00053

TTC00054

TTC00055

 


Sample Multi-spectral Image Mosaics

 

Icaros Photogrammetric Suite

 

  Multi-spectral Image Mosaic of Rural Switzerland (thumbnail)

Camera:  Tetracam ADC Micro 

UAV: eBee by SenseFly  

Mosaicking Software:  Icaros Photogrammetric Suite  *

View Actual JPG Image Mosaic (13.8 MB)

* Able to be tried for one free year and purchased through Tetracam


Agisoft Photoscan Pro

  Multi-spectral Image Mosaic of German Black Grass in Wheat Field (thumbnail)

Camera:  Tetracam Mini-MCA6 with ILS

UAV: Geo-Kopter X-8000 from Geo-Konzept

Mosaicking Software:  Agisoft Photoscan Pro *

Workflow Demostation Paper (pdf): Image Processing with PixelWrench2, Agisoft and QGIS to

monitor black grass patches within wheat fields by Martin Herkommer

* Able to be purchased through Geo-Konzept


Microsoft Image Composite Editor (ICE)

  Multi-spectral Image Mosaic of Desert Property (thumbnail)

Camera:  Tetracam ADC Micro 

UAV: Experimental Prototype Multi-rotor from Monarch

Mosaicking Software:  Microsoft ICE   (Free)

View Actual JPG Image Mosaic (9.3 MB)