Computer Science ›› 2020, Vol. 47 ›› Issue (10): 151-160.doi: 10.11896/jsjkx.190900119

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Remote Sensing Image Processing Technology and Its Application Based on Mask R-CNN Algorithms

LING Chen1, ZHANG Xin-tong2,3, MA Lei2   

  1. 1 Institute of Logistics Science and Technology,Beijing 100166,China
    2 Institute of Automation,Chinese Academy of Science,Beijing 100190,China
    3 School of Artificial Intelligence,Hebei University of Technology,Tianjin 300401,China
  • Received:2019-09-18 Revised:2019-12-11 Online:2020-10-15 Published:2020-10-16
  • About author:LING Chen, born in 1979,B.S.,assistant researcher.His research interests include internet of things and big data intelligence analysis.
    MA Lei,born in 1980,Ph.D,associate professor.His main research interests include intelligent interpretation of remote sensing images.
  • Supported by:
    Youth Program of National Natural Science Foundation of China (61806199)

Abstract: With the development of remote sensing,there are many fields using remote sensing image,such as agriculture,military and so on.At the same time,deep learning,now,is applying in computer vision and image processing widely.It is successful in object detection,classification and semantic segmentation.Unlike fighting ship detection in natural scenes,fighting ships in remote sensing images are overhead views,dense and easy to mix with ports.The main result on fighting ship is taking bounding box as output,which is lacking the mask of the fighting ship,so may not analyzing the weakness in model.Meanwhile,because of the tight fighting ships in remote sensing images,there are easy to have missed detection.For solving the problems,this paper uses Mask R-CNN to detect fighting ships,analyzing training situation and the results of mask and bounding box.By learning the edges of objects and modifying parameter,making model more suitable to fighting ship.After experiment,it can be concluded that the appropriate parameters can effectively reduce the false positive and false negatives caused by compact berthing of fighting ships.

Key words: Deep learning, Image extraction and recognition, Mask R-CNN algorithm, Remote sensing image processing technology, Warship detection

CLC Number: 

  • TP751
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