SBV data reduction
- 1. Sharma, C von Braun, E. M. Gaposchkin
- Journal of Guidance, Control, and Dynamics 23(1…
This paper presents a new method for detecting small moving targets from consecutive image sequences. Image sequences are processed to detect targets, assuming that the data samples have been spatially registered. Firstly, Maximum Value Projection and normalization are utilized to reduce the data samples and reject the background clutter. Then, targets are detected using connected component analysis. At last, the velocities of the targets are estimated by centroid localization and least-square regression. A sliding neighborhood operation is performed before target detection. It can greatly reduce the computation while preserving as much target information as possible. The experimental results indicate that this method can efficiently detect the small moving targets and accurately track their traces. Both centroid locating precision and tracking accuracy are within a pixel.