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http://dx.doi.org/10.7780/kjrs.2004.20.4.275

Classification of Multi-sensor Remote Sensing Images Using Fuzzy Logic Fusion and Iterative Relaxation Labeling  

Park No-Wook (한국지질자원연구원 지질자원정보센터)
Chi Kwang-Hoon (한국지질자원연구원 지질자원정보센터)
Kwon Byung-Doo (서울대학교 지구과학교육과)
Publication Information
Korean Journal of Remote Sensing / v.20, no.4, 2004 , pp. 275-288 More about this Journal
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.
Keywords
Data Fusion; Iterative Relaxation Labeling; Fuzzy Logic; Spatial Information.;
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