智能系统学报
智能繫統學報
지능계통학보
CAAI TRANSACTIONS ON INTELLIGENT SYSTEMS
2013年
6期
512-516
,共5页
李昂%马强%岑翼刚%赵瑞珍%岑丽辉
李昂%馬彊%岑翼剛%趙瑞珍%岑麗輝
리앙%마강%잠익강%조서진%잠려휘
压缩感知%监控视频%关键帧%帧间差值%运动补偿
壓縮感知%鑑控視頻%關鍵幀%幀間差值%運動補償
압축감지%감공시빈%관건정%정간차치%운동보상
compressed sensing%surveillance video%key frame%interframe difference%motion compensation
传统对视频先采样再压缩的方法极大地浪费了硬件资源,针对这一问题,基于压缩感知理论提出了一种对监控视频采样及重构的方法。该方法先获得帧间差值,再将差值投影到小波稀疏域后进行压缩采样。选取每一分组中的中间帧作为关键帧,对关键帧不进行处理,完全保留所有采样点。恢复时利用关键帧和差值可以得到初步重构的视频序列,最后通过运动估计和运动补偿得到优化。实验结果表明,与仅使用压缩感知对差分帧进行重构的方法相比,该方法对监控视频重构帧序列图像的平均峰值信噪比有较大的提升,且受采样点数影响较小,具有很好的鲁棒性。
傳統對視頻先採樣再壓縮的方法極大地浪費瞭硬件資源,針對這一問題,基于壓縮感知理論提齣瞭一種對鑑控視頻採樣及重構的方法。該方法先穫得幀間差值,再將差值投影到小波稀疏域後進行壓縮採樣。選取每一分組中的中間幀作為關鍵幀,對關鍵幀不進行處理,完全保留所有採樣點。恢複時利用關鍵幀和差值可以得到初步重構的視頻序列,最後通過運動估計和運動補償得到優化。實驗結果錶明,與僅使用壓縮感知對差分幀進行重構的方法相比,該方法對鑑控視頻重構幀序列圖像的平均峰值信譟比有較大的提升,且受採樣點數影響較小,具有很好的魯棒性。
전통대시빈선채양재압축적방법겁대지낭비료경건자원,침대저일문제,기우압축감지이론제출료일충대감공시빈채양급중구적방법。해방법선획득정간차치,재장차치투영도소파희소역후진행압축채양。선취매일분조중적중간정작위관건정,대관건정불진행처리,완전보류소유채양점。회복시이용관건정화차치가이득도초보중구적시빈서렬,최후통과운동고계화운동보상득도우화。실험결과표명,여부사용압축감지대차분정진행중구적방법상비,해방법대감공시빈중구정서렬도상적평균봉치신조비유교대적제승,차수채양점수영향교소,구유흔호적로봉성。
The traditional first-compression-then-sampling method used for video greatly wastes hardware resources .In order to solve this problem , a sampling and reconstruction method used for the surveillance video is proposed based on compressed sensing .With this method, first, the interframe difference is calculated and projected to the sparse do -main of the wavelet ,then the wavelet coefficients are sensed by the sensing matrix .The middle frame in every group is taken as the key frame , which is not processed , and all sampling points are completely preserved .In the stage of re-covery , the preliminary reconstruction of the video sequence can be obtained by using the key frames and interframe difference .Finally, the optimization is realized by motion estimation and motion compensation .The experimental re-sults show that , compared with the reconstruction for difference frames by only using compressed sensing , this method can greatly lift the mean peak signal-noise ratio of the sequence image on the reconstruction frames of a surveillance video.In addition, the influence caused by the quantity of the sampling points is small , and the robustness is excel-lent.