衍射光学可变图像去云雾算法的研究与应用  

The diffraction optical variable image to fog research and application of the algorithm

作　　者：于浩[1] 张志利[2] 

机构地区：[1]聊城大学东昌学院,山东聊城252000 [2]天津中德应用技术大学电气与能源学院,天津300350

出　　处：《激光杂志》2017年第3期97-100,共4页Laser Journal

基　　金：天津市应用基础与前沿技术研究计划重点项目(15JCZDJC39000);国家科技支撑计划项目(2015BAK06B04)

摘　　要：衍射光学图像研究领域中针对衍射光学图像去云雾处理的研究,一直被作为衍射光学图像科学研究领域中重要的一项研究项目。近年来,在不断的应用实践中发现,传统衍射光学图像去云雾方法中采用算法存在光线可变度逻辑运算差、图像特征处理检索速度慢、衍射光学可变图像去云雾处理效果差等问题。针对传统衍射光学图像去云雾处理方法存在的问题,提出衍射光学可变图像去云雾算法设计,采用三维一体化设计对传统算法进行改进、优化。分别采用衍射光线性动态分布算法(XIVNW)、像素特征捕捉技术(BJNEF)、雾罩层提取剥离技术对传统算法进行改进升级。通过实验证明,提出的衍射光学可变图像去云雾算法设计具有衍射光学图像去云雾效果好、资源开销少、处理速度快等特点。The diffraction optical image research in the field of study of diffraction optical image to cloud processing,has been as a diffraction optical image in the field of scientific research an important research project. In recent years,found in the continuous application of practice,the traditional method of diffraction optical image to fog used in algorithm variable light of logical operations,image feature retrieval speed is slow,the diffraction optical variable image to cloud the issue such as difference of treatment effect. For traditional diffraction problems of optical image to cloud processing method,the diffraction optical variable image to cloud algorithm design,three-dimensional integrated design of the traditional algorithm was improved and optimized. Respectively（ XIVNW）,using the algorithm of dynamic distribution of diffraction pixel features capture technology（ BJNEF）,fog cover layer extraction and stripping technology to the traditional algorithm was improved to upgrade. The diffraction optical variable image is proved by experiments and diffraction optical image to fog clouds algorithm design has good effect,less resource overhead,processing speed,etc.

关 键 词：衍射 光学 图像 去雾 雾罩层 

分 类 号：TN271[电子电信—物理电子学]