【摘要】：海陸分割是光學(xué)遙感圖像海上目標(biāo)識別過程中一個重要步驟,海陸分割的結(jié)果直接影響下一步目標(biāo)識別的效率和正確率;而遙感數(shù)據(jù)的大量增長,使得圖像處理速度變慢,因此分割算法的執(zhí)行效率變得越來越重要。利用Nvidia開發(fā)的統(tǒng)一計算架構(gòu)CUDA(compute unified device architecture),將海陸分割流程的一系列函數(shù)移植到GPU(graphic processing unit)上進行并行處理,能夠有效提高算法執(zhí)行速度。經(jīng)實驗驗證最終完成2 000×2 000大小的圖片在11 ms內(nèi)的海陸分割處理。該方法能夠滿足對于圖像數(shù)據(jù)的傳輸在25 ms內(nèi)的處理,適合用于建立地面或者航空搭載的"實時"處理平臺。
[Abstract]:Land and sea segmentation is an important step in the process of ocean target recognition in optical remote sensing image. The result of sea and land segmentation directly affects the efficiency and accuracy of target recognition in the next step. Because of the rapid growth of remote sensing data, the speed of image processing becomes slower, so the efficiency of segmentation algorithm becomes more and more important. The unified computing architecture CUDA (compute unified device architecture), developed by Nvidia can transplant a series of functions of sea and land segmentation process to GPU (graphic processing unit) for parallel processing, which can effectively improve the execution speed of the algorithm. The experimental results show that the image with the size of 2 000 脳 2 000 can be segmented within 11 ms. This method can satisfy the processing of image data transmission within 25 ms, and is suitable for the establishment of a "real-time" processing platform on the ground or in aviation.
【作者單位】： 中國科學(xué)院長春光學(xué)精密機械與物理研究所;中國科學(xué)院大學(xué);
【分類號】：TP751
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本文編號：2387936