Proc. SPIE. 5415, Detection and Remediation Technologies for Mines and Minelike Targets IX
KEYWORDS: Signal detection, General packet radio service, Target detection, Signal processing, Detection and tracking algorithms, Land mines, Ground penetrating radar, Spatial resolution, Environmental sensing, Modulation
In this work the detection process of buried objects is presented utilizing Ground Penetrating Radar (GPR). Background removal algorithm is used to obtain the target signature and correlation process is performed to reveal the reflected target energy Then, a detection warning signal is created depending on a special process. In this work, pulsed GPR system with 1 GHz bandwith is used. Scanning speed is 0.33cm/sec in the sweeping direction and this process is repeated in the walking direction with 4 cm spatial resolution.
We present a novel approach to compression of video frames based on the foveation behavior of the human visual system (HSV). Eye fixations on a video frame, as depicted by eye-gaze trace data, define an imaginary region of interest. The perceived resolution of the frame by the human eye depends totally on this eye-gaze (fixation) point. The resolution, then, decreases dramatically with the distance from the fovea. This behavior of the HSV has gained interest in the image and video processing area recently especially in compression of images or video frames. We present an approach where eye-gaze trace data are intergral to the compression process which has demonstrated its usefulness in yielding high compression performance. We partition a video frame into three regions: the inner-most incudes a point of eye-gaze for which we apply lossless compression; an outer region which encompasses the first and for which we apply visually lossless (near-lossless) compression, and finally an outmost region where lossy compression is applied. Because of its low computational complexity, we use the Haar wavelet transform. Preliminary results are promising and show improvement over other methods which are mainly full frame based.