Remote Sensing: Preprocessing and Enhancement

Welcome to this weeks remote sensing topic of image pre-processing and spatial enhancement. This week focuses on acquiring remotely sensed information, utilizing programs like ERDAS Imagine or ArcGIS to modify the image to make its information more readily apparent then what might be available at first glance. This is known as spatial enhancement. To facilitate this weeks objectives of utilizing various filters and image transformations I was supplied with a 2003 Landsat 7 image which had some serious stripping effects due to a Scan Line Corrector error. Exploration using low pass, high pass, and Fourier Transformation led up to the actual work on the below map. Low pass enhancements essentially apply a mean kernel filter to smooth the detailed areas letting larger similarities show through. The opposite of this is a High pass filter which enhances the small details like road patterns. The Fourier Transformation was used as the basis of the processing of the below image which was used to reduce the stripping present in the lower inset.

An inset of the initial image is shown in the lower left with the culminated result of ERDAS Imagine and ArcMAP display in the large screen. Stripping is still prevalent but the result is much cleaner than the original. The information on the map details that a Wedge and Low pass transformations were key to the initial processing, followed by stretched symbology adjustments focusing on histogram display by standard deviation.
All other courses throughout this program so far have given already processed or corrected imagery to this point. This is an excellent intro to what to do to imagery that is not already at usable quality. Stay tuned as this concept is broadened throughout the coming weeks.