Image Enhancement – You’ll be ENVIous of the Results!

Now its all well and good spending half a billion dollars putting a satellite in orbit around earth, but if you can’t effectively use the data that it sends back then what’s the point?!

To complete the practical section of this course, I had to get to grips with the software that was needing to be used. The ENVI software is both the most frustrating and yet brilliant thing I have used thus far at the University. It has the ability to adapt and manipulate satellite imagery so that it becomes useful and can be applied to full effect.

Admittedly, it took me a LONG time to get to grips with even the most simple of tasks, but once I had finally managed to open up one of the images and played around for a while I was able to make simple  true and false colour composite images by assigning different bands to the display colours. By assigning different bands ie. band 4 as NIR, its possible to identify different land cover types based on the reflectance and absorption of the various wavelengths.

true false
Image demonstrating the usefulness of making a false colour composite – the detail of what’s vegetation and what isn’t is much clearer now (Source: Kelcey & Lucieer)

 

One of the simple ways to enhance an image is to use a linear stretch which literally stretches the minimum and maximum data values to the ends whilst rescaling the values between the two points. By using linear stretches on each of the three bands in use, I was able to increase the definition and contrast between, in the case of practical 3, the wetlands and the estuary.

Another image enhancement that could be made is a Histogram Equalisation. Essentially, it reassigns the digital values in the original image so that the brightnesses in the output image are more equally distributed  across the output value range. Different to other stretches, histogram equalisation broadens the peaks and makes the valleys shallower so as to make full use of the data range (Campbell & Wynne, 2011).

 

Histo equ
An example illustrating the benefits of Histogram Equalisation (admittedly not a satellite photo…) (Source: songho.ca)

Fun Fact: The first colour a baby see is red. Because it has the longest wavelength among colours it makes it the easiest colour to process by the developing receptors and nerves in the baby’s eyes!

Visit: crisp.nus.edu.sg for more information on image enhancement!

References:

Campbell, J. B. & Wynne, R. H. (2011), Introduction to remote sensing, 5th edn., New York: The Guilford Press, pp. 120.

Kelcey, J. & Lucieer, A. (2012), Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing, Remote Sensing, 4:5, pp. 1462-1493.

Song, H. A. (2006), Histogram, Available at: http://www.songho.ca/dsp/histogram/histogram.html, (Accessed on: 21st May, 2017).

 

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