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Analysis and Improvement of the Real-Time Segmented Pulse Compression-Detection Algorithm
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作者 YANG Jian-xi 《Journal of Donghua University(English Edition)》 EI CAS 2016年第6期928-932,共5页
Real-Time segmented pulse compression-detection is one of the key technologies of space-borne tracking receiver. Its implementation requires an optimized and dedicated hardware. The real-time processing places several... Real-Time segmented pulse compression-detection is one of the key technologies of space-borne tracking receiver. Its implementation requires an optimized and dedicated hardware. The real-time processing places several constraints such as area occupied, power comumption, and speed. A number of segmented compression techniques have been proposed to overcome these limitations and decrease the processing latency. However, relatively high power loss in the partial field could limit their implementation in many current real-time systems. A good theoretical model was designed with intersection signal accumulation to enhance signal- noise-ratio (SNR) gain of detecting signal in the paper. From the experimental results it is known that this approach works well for pulse compression-detection, which is better suited for implementation in the high performance of current field programmable gate array (FPGA) with dedicated hardware multipliers. 展开更多
关键词 linear frequency modulation(LFM) segmented pulse compression signal-noise-ratio(SNR) gain target detection
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An efficient compressed domain moving object segmentation algorithm based on motion vector field 被引量:4
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作者 刘志 沈礼权 张兆杨 《Journal of Shanghai University(English Edition)》 CAS 2008年第3期221-227,共7页
In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector (MV) field parsed from the compressed video is the only cue used for moving object segmentati... In this paper an efficient compressed domain moving object segmentation algorithm is proposed, in which the motion vector (MV) field parsed from the compressed video is the only cue used for moving object segmentation. First the MV field is temporally and spatially normalized, and then accumulated by an iterative backward projection to enhance salient motions and alleviate noisy MVs. The accumulated MV field is then segmented into motion-homogenous regions using a modified statistical region growing approach. Finally, moving object regions are extracted in turn based on minimization of the joint prediction error using the estimated motion models of two region sets containing the candidate object region and other remaining regions, respectively. Experimental results on several H.264 compressed video sequences demonstrate good segmentation performance. 展开更多
关键词 moving object segmentation compressed domain segmentation motion vector (MV) field
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