Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Classification of Multi-sensor Remote Sensing Images Using Fuzzy Logic Fusion and Iterative Relaxation Labeling

퍼지 논리 융합과 반복적 Relaxation Labeling을 이용한 다중 센서 원격탐사 화상 분류

  • 박노욱 (한국지질자원연구원 지질자원정보센터) ;
  • 지광훈 (한국지질자원연구원 지질자원정보센터) ;
  • 권병두 (서울대학교 지구과학교육과)
  • Published : 2004.08.01
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Abstract

This paper presents a fuzzy relaxation labeling approach incorporated to the fuzzy logic fusion scheme for the classification of multi-sensor remote sensing images. The fuzzy logic fusion and iterative relaxation labeling techniques are adopted to effectively integrate multi-sensor remote sensing images and to incorporate spatial neighboring information into spectral information for contextual classification, respectively. Especially, the iterative relaxation labeling approach can provide additional information that depicts spatial distributions of pixels updated by spatial information. Experimental results for supervised land-cover classification using optical and multi-frequency/polarization images indicate that the use of multi-sensor images and spatial information can improve the classification accuracy.

이 논문은 다중 센서 원격탐사 화상의 분류를 위해 퍼지 논리 융합과 결합된 relaxation labeling 방법을 제안하였다. 다중 센서 원격탐사 화상의 융합에는 퍼지 논리를, 분광정보와 공간정보의 융합에는 반복적인 relaxation labeling 방법을 적용하였다. 특히 반복적 relaxation labeling 방법은 공간정보의 이용에 따른 분류 화소의 변화양상을 얻을 수 있는 장점이 있다. 토지 피복의 감독 분류를 목적으로 광학 화상과 다중 주파수/편광 SAR 화상에 제안 기법을 적용한 결과, 다중 센서 자료를 이용하고 공간정보를 함께 결합하였을 때 향상된 분류 정확도를 얻을 수 있었다.

Keywords

References

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