3 April 2000 Quantitative metric for comparison of night vision fusion algorithms
Author Affiliations +
This paper describes development and testing of a program that provides a quantitative metric for the comparison of night vision fusion algorithms. The user enters into the Metric Program the names of a thermal file, a vision file and the corresponding fused image file. The program assigns a fusion rating to the algorithm based on the following four quantitative tests: information content (ic), vision retention (vr), thermal retention (tr), and the bar to detect black segments. In ic the information content of the fused image is compared with a weighted sum of the vision and thermal images. In vr the number of faint lights that the fused image failed to incorporate is counted. In tr the number of pixels from the thermal file included in the fused image is determined. With some fusion algorithms if one of the sensors is blocked, a black segment appears in that area in the fused image, thus losing the information from the unblocked sensor. To test for this the Metric Program creates a thermal file with three horizontal black bars. The program then allows the user to call the executable file of the algorithm under test. Then the user is asked to examine the fused image. If three pitch-black horizontal bars appear on the image, the algorithm fails the test. While the bar test is invariant to the vision/thermal image pair used, the other tests are not. For this reason it is suggested that an algorithm should be tested with 5 or 6 different image pairs and a mean fusion rating calculated. The program is used to evaluate several different algorithms. Day vision fusion algorithms are also tested.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Esin Ulug, M. Esin Ulug, Claire L. McCullough, Claire L. McCullough, } "Quantitative metric for comparison of night vision fusion algorithms", Proc. SPIE 4051, Sensor Fusion: Architectures, Algorithms, and Applications IV, (3 April 2000); doi: 10.1117/12.381667; https://doi.org/10.1117/12.381667


Back to Top