|
Size: 2333
Comment:
|
Size: 2769
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 24: | Line 24: |
| {{attachment:normCrossCor_resized6-pct.png}} '''F3F1 (Lommel-Seeliger without the 2) Correlation Scores:''' ||'''Processing Step'''||||||'''Correlation Score'''|| || ||'''F3F1 (Lommel-Seeliger without the 2)'''||'''F3F2 (Lommel-Seeliger with the 2)'''||'''F3F3 (Clark and Tikir)'''|| ||20cm Iteration 00|| ||10cm Iteration 00 (post Geometry)|| ||5cm Iteration 00 (post Geometry)|| ||5cm Iteration 10|| ||5cm Iteration 20|| |
TestF3F Photometric Function Sensitivity Test Results
Definitions
CompareOBJ RMS: |
The root mean square of the distance from each bigmap pixel/line location to the nearest facet of the truth OBJ. |
Key Findings
Results and Discussion
Results from testing the three photometric functions split into two groups characterized by differing digital terrain accuracy and model behavior. Sub-tests F3F1 and F3F2 (Lommel-Seeliger photometric function without the 2 and with the 2 respectively) performed well with minor differences in the measurements of accuracy, whereas sub-test F3F3 (Clark and Tikir photometric function) performed poorly with pervasive degradation of the digital terrain with every processing step conducted. A detailed analysis of the behavior of F3F3 is reported here: Test F3F3 - Analysis.
CompareOBJ RMS
Three CompareOBJ RMS values for the final 5cm resolution 20m x 20m evaluation bigmap are presented for each subtest and each S/C position and camera pointing uncertainty:
- The largest CompareOBJ RMS (approx. 65cm across subtests) is obtained by running CompareOBJ on the untranslated and unrotated evaluation model.
- The second smallest CompareOBJ RMS (approx. 15cm across subtests) is obtained by running CompareOBJ with its optimal translation and rotation option.
- The smallest CompareOBJ RMS (approx. 9cm across subtests) is obtained by manually translating the evaluation model and searching for a local CompareOBJ RMS minimum.
The CompareOBJ optimal translation routine is not optimized for the evaluation model scale (5cm pix/line resolution). Manual translations of the bigmap were therefore conducted in an attempt to find a minimum CompareOBJ RMS. The manually translated evaluation models gave the smallest CompareOBJ RMSs.
Normalized Cross Correlation Scores
F3F1 (Lommel-Seeliger without the 2) Correlation Scores:
Processing Step |
Correlation Score |
||
|
F3F1 (Lommel-Seeliger without the 2) |
F3F2 (Lommel-Seeliger with the 2) |
F3F3 (Clark and Tikir) |
20cm Iteration 00 |
|||
10cm Iteration 00 (post Geometry) |
|||
5cm Iteration 00 (post Geometry) |
|||
5cm Iteration 10 |
|||
5cm Iteration 20 |
|||
The evaluation maps were compared with a truth map via a cross-correlation routine which derives a correlation score. As a guide the following scores show perfect and excellent correlations:
- A map cross-correlated with itself will give a correlation score of approx. 1.0;
- Different sized maps sampled from the same truth (for example a 1,100 x 1,100 5cm sample map and a 1,000 x 1,000 5cm sample map) give a correlation score of approx. 0.8.