校园航拍图像超分辨率重建的粒计算方法  

Granular Computing for Super-Resolution Reconstruction of Aerial Images in Campus

作　　者：刘宏兵 马原 刁小宇 郭华平[3] LIU Hongbing;MA Yuan;DIAO Xiaoyu;GUO Huaping(Network Information and Computing Center, Xinyang Normal University, Xinyang 464000, China;College of Computer and Information Technology,Xinyang Normal University, Xinyang 464000, China;College of Information Engineering, Xinyang Agriculture and Forestry University, Xinyang 464000, China)

机构地区：[1]信阳师范学院网络信息与计算中心,河南信阳464000 [2]信阳农林学院信息工程学院,河南信阳464000 [3]信阳师范学院计算机与信息技术学院,河南信阳464000

出　　处：《信阳师范学院学报（自然科学版）》2019年第2期312-319,共8页Journal of Xinyang Normal University(Natural Science Edition)

基　　金：国家自然科学基金项目(61170202);河南省科技计划项目(182300410145;182102210132)

摘　　要：提出了校园航拍图像超分辨率重建的粒计算方法,包括:(1)提出了图像粒化方法,实现图像空间向粒度空间的转化;(2)设计粒之间合并运算和分解运算,构造粒之间的模糊包含关系μ和σ,实现不同粒度空间之间的转化,获取图像的先验知识,指导校园航拍图像超分辨率重建算法的设计;(3)根据自顶向下、自底向上两种模式和图像先验知识,设计校园航拍图像超分辨率重建粒计算算法,实现粒度空间向图像空间的转化.实验验证了提出方法的可行性.Granular Computing (GrC) is proposed for super-resolution reconstruction of aerial images in campus.(1) The granulation method of image is proposed to transform the image space into granularity space.(2) The join operation and the meet operation between two granules are designed for the fuzzy inclusion measure μ and σ between two granules, which are used to realize the transformation between two granularity spaces with different granularities, to obtain the prior knowledge to guide the design of super-resolution reconstruction algorithms.(3) According to up-down and bottom-up computing models, the granular computing algorithms of image super-resolution reconstruction are designed to realize the transformation from granularity space to image space in terms of the prior knowledge. The proposed algorithms are verified by the experiments.

关 键 词：低分辨率图像 高分辨率图像 粒计算 超分辨率重建 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]