Target Detection in Foveal ATR Systems
Abstract
Automatic target recognition (ATR) applications require simultaneously a wide field of view (FOV) for better detection and situation awareness, high resolution for target recognition and threat assessment, and high frame rate for detecting brief events and disambiguating frame-to-frame correlation. Uniformly sampling the entire FOV at recognition resolution is simply wasteful in ATR scenarios with localized regions of interest (ROIs). Foveal data acquisition with space-variant sampling and context-sensitive sensor articulation is highly optimized for active ATR applications. We propose a multiscale local Zernike filter-based front end target detection technique for a commercially feasible foveal sensor topology with piecewise constant resolution profile. Anisotropic heat diffusion is employed for preprocessing of the foveal data. Expansion template matching is used to derive a detection filter that optimizes the discriminant signal-to-noise ratio (SNR). Results are presented with simulated foveal imagery, derived from real uniform acuity FLIR data.
Cite
Text
Ghosal and McKee. "Target Detection in Foveal ATR Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1996. doi:10.1109/CVPR.1996.517151Markdown
[Ghosal and McKee. "Target Detection in Foveal ATR Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1996.](https://mlanthology.org/cvpr/1996/ghosal1996cvpr-target/) doi:10.1109/CVPR.1996.517151BibTeX
@inproceedings{ghosal1996cvpr-target,
title = {{Target Detection in Foveal ATR Systems}},
author = {Ghosal, Sugata and McKee, Douglas C.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1996},
pages = {714-719},
doi = {10.1109/CVPR.1996.517151},
url = {https://mlanthology.org/cvpr/1996/ghosal1996cvpr-target/}
}