高分辨率水稻害虫图像采集技术  

High-Resolution Image Acquisition System for Rice Pests

作　　者：刘媛媛 章越海 余桂英 张明月 霍剑锋 张宝武 Liu Yuanyuan;Zhang Yuehai;Yu Guiying;Zhang Mingyue;Huo Jianfeng;Zhang Baowu(College of Metrology and Measurement Engineering, China Jiliang University, Hangzhou, Zhejiang 310018, China;Hangzhou Administration of Quality and Technology Supervision, Hangzhou, Zhejiang 310018, China)

机构地区：[1]中国计量大学计量测试工程学院,浙江杭州310018 [2]杭州市质量技术监督检测院,浙江杭州310018

出　　处：《激光与光电子学进展》2018年第2期193-199,共7页Laser & Optoelectronics Progress

基　　金：浙江省重大科技专项计划(2011C12025)

摘　　要：高分辨率图像的获取是图像模式自动识别的前提和基础。以稻田害虫为对象,研究立体害虫多聚焦成像问题。以Harris角点数和图像熵为图像质量检测标准,采用基于小波变化的图像融合算法,针对不同倍率的稻田害虫图像,分析图像采集时的步进量对图像融合分辨率的影响。通过实验对比,获得最佳的图像采集与图像融合策略,得到放大倍率与最适步进量的关系曲线。实验结果显示,该方法对于立体害虫采集有较好的景深扩展能力,可为建立高质量稻田害虫样本图像数据库提供有效手段。High-resolution image acquisition is the premise and foundation of automatic pattern recognition. We study the multi-focus image acquisition problem of stereoscopic pests, taking the rice field insect as the object. Harris corner detection and image entropy are taken as the image quality detection standard. The influence of step displacement in image acquisition on the resolution of image fusion is analyzed with image fusion method based ort wavelet transform for different scales of rice pest images. According to the experimental comparison, we obtain the best image acquisition and image fusion strategy and the relation of magnification and optimum step displacement. The experimental results show that this strategy is reliable to acquire the extended-depth-of-field image for stereoscopic pests, which provides an effective measure for establishing a high-quality image database of rice pest samples.

关 键 词：图像处理 图像采集 图像融合 水稻害虫 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]