Earticle

초록

영어

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

목차

I. 서론
 II. Rough 집합이론을 이용한 다중 분광 이미지 데이터의 밴드 분류
  1. Rough 집합이론
  2. Rough 집합이론을 이용한 밴드 분류
 III. 실험 및 결과의 고찰
  1. 실험대상 선정
  2. 학습 데이터들의 분포 특성
  3. 실험 데이터들의 분포 특성
  4. Rough 집합이론을 이용한 밴드 분류
  5. 특수한 분포를 갖는 데이터들의 밴드 분류
  6. 실험 결과의 평가
 IV. 결론
 참고문헌
 Abstract

저자

• 원성현 [ Won, Sung-hyun | 지산대학 전자계산과 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  경영과 정보연구 [Management Information Systems review]

• 간기

  계간

• pISSN

  1598-2459

• 수록기간

  1997~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 325 DDC 658