Paper
24 August 2006 Millimeter-wave video sequence denoising and enhancement in concealed weapons detection application
Author Affiliations +
Abstract
In this paper, we present an adaptive algorithm to improve the quality of millimeter-wave video sequence by separating each video frame into foreground region and background region, and handle them differently. We separate the foreground from background area by using an adaptive Kalman filter. The background is then denoised by both spatial and temporal algorithms. The foreground is denoised by the block-based motion compensated averaging, and enhanced by wavelet-based multi-scale edge representation. Finally further adaptive contrast enhancement is applied to the reconstructed foreground. The experimental results show that our algorithm is able to produce a sequence with smoother background, more reduced noise, more enhanced foreground and higher contrast of the region of interest.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaohui Wei, Hua-Mei Chen, and Ishfaq Amad "Millimeter-wave video sequence denoising and enhancement in concealed weapons detection application", Proc. SPIE 6312, Applications of Digital Image Processing XXIX, 631208 (24 August 2006); https://doi.org/10.1117/12.678616
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication and 1 patent.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Denoising

Extremely high frequency

Weapons

Electronic filtering

Filtering (signal processing)

Detection and tracking algorithms

Back to Top