Image Analysis

##Infrared compositing## If you have [near-infrared imagery](/tool/near-infrared-camera) you can composite that imagery with the visible-light imagery to see how healthy the vegetation is. * [NDVI and NRG compositing](/wiki/ndvi) * [Video: Creating infrared composites of aerial wetlands imagery]( - Learn to combine infrared and visible-light photographs (taken from balloon photography) to produce an "NRG" composite, where reddish color indicates photosynthesis. * [Video: Creating false-color NDVI with aerial wetlands imagery]( - Learn to use the open-source GIMP application to create a Normalized Differential Vegetation Index image from infrared and visible-light aerial photographs. Also explore false-color techniques for presenting the data. ##Contrast adjustments## Stretch the contrast and saturation of your images to see more detail, especially underwater. Read more here: * ###Decorrelation stretching### _Nathan Craig writes:_ Decorrelation stretching may be a method to consider. Various flavors of the transformation are easily run using the DStretch Plugin for Image J. Several that seemed to represent variability relevant to the case study are included. I use DStretch to help bring out detail in rock art scenes that are highly eroded. However, the method has utility outside of rock art studies. It may be an additional approach to consider when trying to identify pollution or other contaminants. Here is information on DStretch Here is a paper that describes the transformation [Browse more of these]( ##Classification## Using the ratios of Red, Green, and Blue (and possibly Near-infrared), spectral classification attempts to categorize regions of an image by land type. ###Read more on the [classification page »](/wiki/classification)### ### Image Analysis [activities:image-analysis]...

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