CAJ | 학술논문

应用纹理特征进行影像分类,关键在于纹理特征参数的确定。以洪泽湖湿地典型地区为研究对象,选择灰度共生矩阵进行纹理特征计算,探讨灰度共生矩阵窗口尺寸、移动步长、方向和纹理特征统计量对淡水湖泊湿地的区分能力；然后,利用纹理特征和地物光谱特征,结合决策树方法对研究区湿地及其他主要地类进行分类,并通过混淆矩阵进行精度评价。结果表明：研究区湿地分类中纹理特征的最佳窗口大小为3像元×3像元,方向为90°,步长为1个像元,纹理特征统计量组合为均值、熵和相关度；分类精度为83.24%,Kappa为0.788,其结果验证了纹理特征参数选择的科学性和合理性。
응용문리특정진행영상분류,관건재우문리특정삼수적학정。이홍택호습지전형지구위연구대상,선택회도공생구진진행문리특정계산,탐토회도공생구진창구척촌、이동보장、방향화문리특정통계량대담수호박습지적구분능력；연후,이용문리특정화지물광보특정,결합결책수방법대연구구습지급기타주요지류진행분류,병통과혼효구진진행정도평개。결과표명：연구구습지분류중문리특정적최가창구대소위3상원×3상원,방향위90°,보장위1개상원,문리특정통계량조합위균치、적화상관도；분류정도위83.24%,Kappa위0.788,기결과험증료문리특정삼수선택적과학성화합이성。
The determination of parameters for texture analysis is crucial to remote sensing image classification. In this paper, the Hongze Lake wetlands were taken as the study area and the texture was calculated based on gray level co-occurrence matrix. The effect of the window size, moving step and direction in computing texture upon the separability of freshwater lake wetlands was discussed. The classification of wetlands was carried out based on decision tree classification by using texture and spectral features. The classification accuracy was assessed based on error matrix. It is shown that the parameters of 3 pixel × 3 pixel in the direction of 90° are the optimal ones. Mean, entropy, correlation are used for the classification of wetlands in the study area. The classification accuracy is 83 . 24% with Kappa of 0 . 788 . The results show that the effect of texture parameters upon the classification of freshwater lake wetlands is significant.