基于多层次模糊综合评判的高分影像质量评价

发布时间：2018-06-29 21:44

本文选题：高分影像 + 多层次模糊综合评判　；参考：《北京邮电大学》2017年硕士论文

【摘要】：随着我国高分一号卫星的发射,高分影像数据已经发展成为我国影像数据的主要来源,它的质量对于数据交换、共享和使用都有很大的影响,同时也将直接影响着GIS应用、分析、决策的正确性和可靠性,因此高分影像质量问题越来越受到广大用户的关注。如何科学、客观、全面、公正地评价高分影像质量,区别出高分影像的质量等级,确保高分影像专题产品有效服务于国民经济发展和国防建设至关重要。本文针对高分影像的质量评价问题,主要的研究工作如下:1.高分影像质量评价指标体系的构建。将两层模糊综合评判方法引入高分影像质量的综合评价中,以高分一号卫星影像作为典型案例,通过分析国内外现有的质量评价指标体系,并结合我国高分影像数据自身的特点,构建了高分影像质量评价指标体系,具体包括了栅格质量、数学精度、逻辑一致性、属性精度、附件质量和表征质量六个方面一级评价指标和23个二级评价指标,为高分影像质量评价分析提供了基础。2.多层次模糊综合评判模型的构建。由于传统的方法在影像的模糊属性方面有很多不足,不能全面合理地对其做出评价。本文提出采用多层次模糊综合评判的方法并完成了其评判模型的构建,并基于层次分析法和三角形分布隶属函数分别对因素集的权重和隶属度进行了定量分析,克服了空间数据自身存在的随机和模糊不确定性以及现有研究中缺乏定量分析的问题。3.高分影像质量评价实例分析。依托高分城市精细化管理遥感应用示范系统项目,运用多层次模糊综合评判模型对代表平原丘陵地区的霍山县小城镇和山区的黄山风景名胜区高分影像分别进行实例分析,得出了两地高分影像质量的评语等级均为“良好”,评价结果与项目的实际情况基本符合。运用模糊综合评判法对高分影像质量进行评价是一种比较科学的方法。它不仅能够对平原丘陵地区的影像质量进行准确地分析,而且对山区的影像质量也有很好的划分,具有很好的使用价值。
[Abstract]:With the launch of high score 1 satellite in China, high score image data has developed into the main source of image data in China. Its quality has great influence on data exchange, sharing and use, and will also directly affect the application of GIS. Because of the correctness and reliability of the analysis and decision making, the problem of high score image quality has been paid more and more attention by users. How to scientifically, objectively, comprehensively and fairly evaluate the quality of high score image, distinguish the quality grade of high score image and ensure that the special product of high score image can effectively serve the development of national economy and national defense construction is very important. The main research work of this paper is as follows: 1. The construction of high score image quality evaluation index system. The two-layer fuzzy comprehensive evaluation method is introduced into the comprehensive evaluation of the high score image quality. Taking the high score 1 satellite image as a typical case, the existing quality evaluation index system at home and abroad is analyzed. Combined with the characteristics of high score image data in China, the evaluation index system of high score image quality is constructed, which includes grid quality, mathematical accuracy, logical consistency, attribute accuracy, and so on. The first grade evaluation index and 23 second grade evaluation index in the six aspects of annex quality and representation quality provide the basis for high score image quality evaluation and analysis. The construction of multi-level fuzzy comprehensive evaluation model. Because the traditional method has many deficiencies in the fuzzy attribute of image, it can not be evaluated comprehensively and reasonably. In this paper, a multi-level fuzzy comprehensive evaluation method is proposed and its evaluation model is constructed, and the weight and membership degree of the factor set are quantitatively analyzed based on AHP and triangular distribution membership function, respectively. It overcomes the random and fuzzy uncertainty of spatial data and the lack of quantitative analysis in existing research. A case study of high score image quality evaluation. Relying on the high-score city fine management remote sensing application demonstration system project, the multi-level fuzzy comprehensive evaluation model is used to analyze the high-score images of small towns in Huoshan County and Huangshan scenic spots in mountainous areas, which represent the plain and hilly areas. It is concluded that the evaluation grade of high score image quality is "good", and the evaluation results are basically consistent with the actual situation of the project. It is a scientific method to evaluate the quality of high score image by fuzzy comprehensive evaluation method. It can not only accurately analyze the image quality of the plain and hilly area, but also have a good classification of the image quality of the mountain area.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP751

【参考文献】