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논문검색

A Remote Sensing Industrial Solid Waste Image Segmentation Method Based on Improved Watershed Algorithm

초록

영어

Taking the high-resolution remote sensing image of industrial waste dump as the research object, this paper proposes a new image segmentation method based on marker-controlled watershed transform and region merging. The method gets the finial partition result by two-phrase segmentation on the pan-sharpened true color ALOS image. In the first phase, color gradient image of original image should be calculated and then it is modified by morphological impose minima, which should use markers extracted in two different ways. Lastly, preliminary segmentation result is obtained by watershed transform operates on the modified color gradient image. To solve the over-segmentation of industrial solid waste and other ground objects, region merging operation is performed according to the similarity measure criterion based on segmented objects’ color histogram Bhattacharyya coefficient in the second phrase, and then the final result is obtained. This method has been tested on the pan-sharpened ALOS image of 2.5 meters resolution in Shizuishan industrial zone, China. Experiment results demonstrate that this method is feasible and effective to segment the remote sensing industrial solid waste image.

목차

Abstract
 1. Introduction
 2. Segmentation based on Marker-controlled Watershed and Region Merging
  2.1. Morphological Color Gradient Calculation
  2.2 Marker Extraction
  2.3 Watershed Transform
  2.4 Region Merging
 3. Experiment and Analysis
  3.1 Experiment Data and Environment
  3.2 Experimental Procedures
  3.3 Experimental Results
  3.4 Results Analysis
 4. Conclusion
 Acknowledgements
 References

저자정보

  • Wenxing Bao School of Computer Science and Engineering, Beifang University of Nationalities, Yinchuan Ningxia 750021, P. R. China
  • Bing Yu School of Computer Science and Engineering, Beifang University of Nationalities, Yinchuan Ningxia 750021, P. R. China

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