波段比算法结合高光谱图像技术检测柑橘果锈

Detection of rust in citrus by hyperspectral imaging technology and band ratio algorithm

为克服柑橘表面不平整导致光线反射不均匀的影响,研究提出了波段比算法,使高光谱图像技术能够快速有效地检测柑橘果锈。首先根据Sheffield指数(SI)确定最佳波段(625nm和717nm),经比值变换后得到第一幅比值图像;然后选取特征波长625nm的邻近波段(621nm),与其比值变换后得到第二幅比值图像,提取轮廓,构建掩膜以消除第一幅比值图像的背景噪声,最后进行阈值分割和数字形态学运算,完成果锈区域的特征检测。试验结果表明,基于波段比算法的高光谱图像技术可有效检测柑橘果锈,检测率达到92%。研究表明波段比算法在高光谱图像技术快速无损地检测柑橘果锈中,能够有效地降低光照反射不均匀的影响,增强谱间差异,提高检测的精度。

Hyperspectral imaging technology was attempted to detect rust in citrus in this study, and band ratio algorithm was proposed to overcome the adverse effects of uneven reflectance intensity due to curvature of spherical objects. First, Sheffield Index was used to determine two optimal bands （i.e. 625 nm and 717 nm）, and the first ratio image was obtained by ratio transformation between them. Next, the optimal band with 625 nm and its neighbor band with 621 nm were performed to ratio transformation, and the second ratio image was obtained to build the mask. Then, the background noise of the first ratio image was removed by the mask. Finally, rust features on the surface of citrus were extracted by threshold segmentation and morphological image processing. The experimental results show that the rust in citrus can be detected with an accuracy of 92% by hyperspectral imaging technology and band ratio algorithm. This work demonstrates that band ratio algorithm was able to effectively reduce the adverse effects of uneven reflectance intensity, maximize the differences between bands, and improve the performance in detection of rust in citrus by hyperspetral imaging technology.