In the previous chapters, we discussed imaging technology and remote sensing systems. Once the data reach the ground, the next question is how to extract information from the images. We'll begin with traditional photo-interpretation techniques, then move on to the manipulation of digital data.
There are two techniques involved in image processing for remote sensing: enhancing images for presentation and extracting information. Most work at the pixel level and many make use of scene statistics. If the data inhabit more than one spectral dimension (that is, if they have color), then a broad range of techniques can exploit their spectral character and extract information.
Traditional image analysis makes use of certain key elements of recognition, ten of which are developed here. The first four - size, shape, height, and shadow - are related to the geometry of objects in the scene.
Shape is one of the most useful elements of recognition. One classic shape-identified structure is the Pentagon, shown earlier in Fig. 3.7. In Fig. 3.6, shape alone can identify the airfield, though it is not well resolved. Other instantly recognizable shapes include oval racetracks and the pyramids of Egypt.
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