CAJ | 학술논문

为了解决利用单一特征对彩色遥感图像进行分类效果不理想、普适性不强等问题，提出了一种基于颜色和纹理特征组合的支持向量机彩色遥感图像分类方法。该方法尝试将彩色遥感图像的颜色信息和纹理信息相结合作为支持向量机算法分类的特征向量，据此对遥感影像进行分类，并进行了实验验证。结果表明，颜色和纹理特征组合的支持向量机分类方法能够取得较高的分类精度，其分类效果优于传统的单一颜色或纹理特征分类，是一种有效的彩色遥感图像分类方法。
위료해결이용단일특정대채색요감도상진행분류효과불이상、보괄성불강등문제，제출료일충기우안색화문리특정조합적지지향량궤채색요감도상분류방법。해방법상시장채색요감도상적안색신식화문리신식상결합작위지지향량궤산법분류적특정향량，거차대요감영상진행분류，병진행료실험험증。결과표명，안색화문리특정조합적지지향량궤분류방법능구취득교고적분류정도，기분류효과우우전통적단일안색혹문리특정분류，시일충유효적채색요감도상분류방법。
In order to improve the classification results and solve the universality in color sensing image classification using unique feature , a new support vector machine ( SVM) color remote sensing image classification algorithm based on color feature and texture feature combination was proposed .The method used the combination of the color information and the texture information of color remote sensing image as the eigenvectors of SVM algorithm .The results show that the method can achieve higher precision compared with the traditional method using unique feature or texture feature .The method is effective to classify the remote sensing image .