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RESULTS<br />

The <strong>image</strong> <strong>fusion</strong> between the Quickbird PAN <strong>image</strong> <strong>and</strong> the MS <strong>image</strong> was successful <strong>using</strong> the Ehlers <strong>and</strong> the<br />

SRM pan sharpening algorithms. The fused <strong>image</strong>s provide some definite advantages for combining high spatial<br />

<strong>and</strong> high spectral resolution <strong>image</strong>ry. One major difference between the fused <strong>image</strong>s <strong>and</strong> the original MS <strong>image</strong> is<br />

the pixel resolution, where the fused <strong>image</strong>s have a 65 cm resolution compared <strong>to</strong> the original MS <strong>image</strong> at 2.5<br />

meters. Consequently, this resulted in different pixel <strong>classification</strong>s for each <strong>image</strong> based on the roof training class.<br />

A sub-pixel classifier was used <strong>to</strong> identify all of the pixels in the <strong>image</strong> that are of the same category of roof training<br />

class. Table 2 summarizes the percentage of correct pixels, based on 10 r<strong>and</strong>omly selected roof structures spread<br />

throughout the scene, for each original MS <strong>image</strong> <strong>and</strong> each fused <strong>image</strong>. Table 3 shows the percentages of incorrectly<br />

identified pixels, based on a different 10 r<strong>and</strong>om locations spread throughout the scene. The percentages<br />

were estimated by visual quantative analysis of each area.<br />

Table 2. Percentage of Correctly Identified Pixels<br />

Location Original MS<br />

Image<br />

Ehlers Fusion SRM Fusion<br />

1 55 95 80<br />

2 60 95 80<br />

3 45 90 70<br />

4 90 95 85<br />

5 80 95 90<br />

6 60 80 50<br />

7 60 50 55<br />

8 40 95 75<br />

9 85 95 65<br />

10 20 80 10<br />

Average % Correct 60% 87% 66%<br />

Table 3. Percentage of IN-Correctly Identified Pixels<br />

Location Original<br />

MS Image<br />

Ehlers Fusion SRM Fusion<br />

1 80 90 85<br />

2 85 70 80<br />

3 5 60 5<br />

4 75 55 0<br />

5 0 0 0<br />

6 70 50 5<br />

7 5 0 0<br />

8 0 10 0<br />

9 0 5 5<br />

10 0 0 0<br />

Average % IN-Correct 32% 34% 18%<br />

Table 2 indicates the Ehlers Fusion algorithm outperformed the SRM method <strong>and</strong> the original MS <strong>image</strong> by a<br />

significant margin, based on the average percentage of correctly identified pixels. The SRM method did marginally<br />

better than the original MS <strong>image</strong>, even though the spatial resolution is much better. It is important <strong>to</strong> remember the<br />

fused <strong>image</strong>s have a pixel resolution of 65 cm, whereas, the original MS <strong>image</strong> is at 2.5 meters. So, it is conceivable<br />

Pecora 18 –Forty Years of Earth Observation...Underst<strong>and</strong>ing a Changing World November 14 – 17,<br />

2011Herndon, Virginia

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