SHIP INFRARED OBJECT SEGMENTATION BASED ON MEAN SHIFT FILTERING AND GRAPH SPECTRAL CLUSTERING
DOI:
Author:
Affiliation:

Clc Number:

TP301.6

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    A novel thresholding algorithm was presented to achieve an improved ship infrared object segmentation performance.The proposed algorithm uses discontinuity preserving smoothing algorithm based on mean shift procedure to filter the powerful noise without the loss of the ship object information.The regions produced by mean shift filtering can be represented by a planar weighted region adjacency graphs that incorporates topological information of the image structure and region connectivity.Under the graph representation,region merging algorithm based on SST-minimax was applied to partition the regions into different class,such as sky background,sea background and ship object.Due to the less nodes produced by the regions of filtered image than the original image,the region merging based on SST-minimax algorithms has much less computational complexity.A large number of examples are presented to show the superior performance of the proposed ship infrared object segmentation algorithm.

    Reference
    Related
    Cited by
Get Citation

TAO Wen-Bing, JIN Hai. SHIP INFRARED OBJECT SEGMENTATION BASED ON MEAN SHIFT FILTERING AND GRAPH SPECTRAL CLUSTERING[J]. Journal of Infrared and Millimeter Waves,2007,26(1):61~64

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:December 21,2005
  • Revised:June 18,2006
  • Adopted:
  • Online:
  • Published: