Proceedings Article | 19 May 2006
KEYWORDS: Sensors, Video, Cameras, Automatic target recognition, Image compression, Visualization, Image quality, Video compression, Data communications, Eye
A lot of efforts have been pursued in Automatic Target Recognition (ATR), including, based on: Fourier transform,
wavelet transform, novelty filtering, and many others. Unfortunately, in all these methods, a target, either on-the-move
(OTM), or static, has to already be identified. Such a Target Identification (ID) pre-ATR process, however, requires
significant data reduction that must be done before the ATR process starts. The pre-ATR ID process becomes complex
if it is performed by RF-wireless visual sensor networks, based on Unmanned Ground Vehicles (UGVs), or other ground
vehicles. The visual sensors include: TV cameras, artificial animal eyes [1] (fish eye, bug eye, lobster eye [2], etc.), and
other video-like sensors. These sensors need to work not only autonomously
autonomously, but also in cooperation , through RFwireless
inter-communication which should be continuous
to preserve constant cooperation. Such constant video
communication should avoid video image breakdown (in the form of heavy pixeling, or complete image blackout) under
abrupt worsening of digital data transfer conditions, in terms of increasing environmental noise (or, reducing SNR),
and/or increasing of BER (bit-error-rate) of the video signal transfer. Thus, replacement of image breakdown by its
graceful degradation (i.e., preserving image continuity at the expense of quality reduction) is a central issue of the realtime
pre-ATR video data reduction.
In this paper, we will first discuss the conditions of continuous video RF-communication, based on graceful image
degradation, and then analyze some important examples of the real-time pre-ATR video data reduction, based on
cooperative video networks, with TV-cameras, as visual sensors.
