卫星海量数据背景下遥感图像去噪算法研究

发布时间：2018-05-22 07:35

本文选题：图像压缩 + 图像去噪　；参考：《长春理工大学》2017年硕士论文

【摘要】：近年来,我国发射了大量卫星,从北斗导航系列卫星到各种气象、资源勘探卫星,可以说,我国的航天遥感技术取得了长足发展。伴随着这么多的卫星发射升空,每天都有海量的数据从各种传感器上接收下来。与此同时,在采集和回传阶段,数据或多或少都会受到许多不确定因素的影响而被污染。因此,在传输前对其进行压缩,以及在接收后进行噪声去除已成为广泛关注的研究热点。小波分析的时频局部特性和多分辨率分析特性,可以把图像数据中的重要信息有效地提取出来,因此,它在图像处理领域得到了非常广泛的应用。文章的主要工作是把接收到的图像数据经小波变换后如何更好地对其进行噪声剔除,以及图像传输前的数据压缩。小波变换去噪的方法已有很多种,本文着重考虑阈值去噪方法,讨论了去噪过程中阈值和阈值函数的选取,并对传统方法进行了改进,最后通过仿真,检验了改进方法的可行性及去噪效果。分析了经典小波编码算法,针对SPIHT编码算法需要大的存储空间和很多不必要运算的缺点,提出了一种改进的SPIHT编码算法,弥补了之前编码过程中需要大存储空间并耗时的不足。
[Abstract]:In recent years, China has launched a large number of satellites, from Beidou navigation series satellites to various meteorological and resource exploration satellites. It can be said that China's space remote sensing technology has made great progress. With so many satellite launches, huge amounts of data are received from various sensors every day. At the same time, at the stage of collection and return, the data are more or less polluted by many uncertain factors. Therefore, compression before transmission and noise removal after receiving have become the focus of attention. The time-frequency and multi-resolution characteristics of wavelet analysis can effectively extract important information from image data, so it has been widely used in the field of image processing. The main work of this paper is how to eliminate the noise of the received image data after wavelet transform, and how to compress the data before the image transmission. There are many kinds of denoising methods based on wavelet transform. This paper focuses on the threshold denoising method, discusses the selection of threshold and threshold function in the process of de-noising, and improves the traditional method. The feasibility of the improved method and the effect of denoising are tested. This paper analyzes the classical wavelet coding algorithm, aiming at the disadvantages of SPIHT coding algorithm which needs large storage space and many unnecessary operations, an improved SPIHT coding algorithm is proposed, which makes up for the shortage of large storage space and time consuming in the previous coding process.
【学位授予单位】：长春理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP751

【参考文献】