黄瓜霜霉病害的窄带多光谱图像光谱分类和评估研究  

Study on Spectral Classification and Evaluation Base on Narrowband Multispectral Images of Cucumbers Downy Mildew Disease

作　　者：李泽东[1,2] 李宏宁 方玉萍[3] 窦爱丽[1] 易琪[1] 盛宽智[1] 杨卫平[1] 冯洁[1] 

机构地区：[1]云南师范大学物理与电子信息学院,云南昆明650092 [2]云南师范大学太阳能研究所,云南昆明650092 [3]云南师范大学职业技学术教育院,云南昆明650092

出　　处：《云南师范大学学报（自然科学版）》2011年第6期63-69,共7页Journal of Yunnan Normal University:Natural Sciences Edition

基　　金：国家自然科学基金资助项目(60968001;60768002);云南省自然科学基金资助项目(2009CD047);云南省大学生创新实验(CX07)

摘　　要：在研究多光谱成像技术特点的基础上,提取光谱有效特征信息,优化光谱编码条件,对4个等级的黄瓜霜霉病害叶面光谱进行融合编码分类识别,可以有效地降低光谱的相似性,增强可分性,实现了4个病害等级的较好分类。在编码识别的基础上,采用一种权衡性较强的评价方法对分类结果进行评估,这种评价方法实现了把病害分类由4个离散的等级扩展到从0到1的连续量化的评定,并且可以精确到对单个像素点的等级评估。Based on the study of Multi-spectral imaging technology,we extracted spectral effective feature information and optimize coding conditions.In this paper,a fusion coding for spectrum method was presented.Classification and recognition of four levels of cucumber downy mildew was achieved by fusion coding for the spectrum of foliar disease.The result of classification showed that the spectral similarity was reduced effectively and the separability was enhanced by fusion coding.Then,an evaluation method was adopted to evaluate the result of classification in this paper.The evaluation method expanded disease rating levels from four discrete classificationlevel to continuous and quantifiable level ranging in between 0 and 1.The quantification accuracy reached to the pixels level.

关 键 词：多光谱成像技术 光谱特征 光谱编码 加权归类 病害评估 

分 类 号：O433.5[机械工程—光学工程]