Module 6: Image Enhancement

This week we covered Radiometric Correction or Enhancements to account for effects of sensor-detector-and platform, atmospheric and illumination effects, and terrain effects.  We also looked at Spatial Enhancements with Pan-Sharpening (merging a panchromatic image at high resolution with an image at lower resolution) and spatial filters.  We were presented with:  types of radiometric effects that can impact remotely sensed data, differences between absolute and relative atmospheric correction, pan sharpening, convolution filter (high and low pass filters), and Fourier transform.

This week in lab we walked through the steps of downloading and importing satellite imagery from https://glovis.usgs.gov/  (which wasn't loading properly at the time), performed spatial enhancements in ArcMap and ERDAS and utilized Fourier Transform function.  The goal of the above image was to restrict the striping impact of the image while keeping the detail of the image.  I don't think mine is a very good example.  This was much more difficult and felt more of an art than a science.  The lab instructions included several enhancement techniques, a wedge mask, a low pass filter and then a sharpening.  From there the direction was our own.  I applied another low pass filter of 5X5 in addition to the 3X3 we used earlier and then sharpened again.  The second sharpening did not seem to enhance as much as the earlier.  And although the additional low pass toned down the striping I feel I lost significant detail in the process.  Previous to this exercise I would have though that image correction would involve specific calculations and then transformations to correct.  This was not my experience with this lab.  It was more of trial and error.  Maybe this changes with more experience or maybe the experiences shape the decisions of how to correct.