Automatic Thresholding Techniques for Sar Images

نویسندگان

  • Moumena Al-Bayati
  • Ali El-Zaart
  • Xiaoli Tian
  • Shuiping Gou
چکیده

Segmentation of Synthetic Aperture Radar (SAR) images have a great use in observing the global environment, and in analysing the target detection and recognition .But , segmentation of (SAR) images is known as a very complex task, due to the existence of speckle noise. Therefore, in this paper we present a fast SAR images segmentation based on between class variance. Our choice for used (BCV) method, because it is one of the most effective thresholding techniques for most real world images with regard to uniformity and shape measures. Our experiments will be as a test to determine which technique is effective in thresholding (extraction) the oil spill for numerous SAR images, and in the future these thresholding techniques can be very useful in detection objects in other SAR images.

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تاریخ انتشار 2013