摘要光学遥感图像的信噪比是光学遥感器所获取数据质量的一个重要评价标准。使用图像法估算光学遥感图像的信噪比是一种常用方法。本文首先介绍了信噪比的概念和光学遥感图像噪声，接着指出评价遥感图像信噪比是重要而有意义的一项工作。然后，论文详细介绍了一些经典的光学遥感图像信噪比估算方法和优化算法。最后，论文通过对模拟图像和实际图像的信噪比估算结果进行对比，分析出各种方法的优点和缺点。将经典算法和优化算法对比后发现，后者的健壮性显著提高，并且估算的信噪比结果更加准确。总而言之，只有合理、准确地应用各种方法对各类光学遥感图像进行信噪比估算，才能达到事半功倍的目的。62980

毕业论文关键词  图像噪声；信噪比估算；图像分块；局部标准差；去相关

毕业设计说明书（论文）外文摘要

Title      Signal-to-noise Ratio Estimation of Optical Remote  Sensing Imagery Based on Image Method                          

Abstract The signal-to-noise ratio is one of the most important indices which can be used to evaluate the data quality obtained by a remote sensor. It is a commonly used method to estimate the SNR of optical remote sensing imagery based on image method. First, the paper introduces the concept of signal-to-noise ratio and the noise of the optical remote sensing imagery. Second, the paper shows it is very important and meaningful to assess the SNR of a remote sensing imagery. Then, the paper presents some typical methods and improved methods for SNR estimation of optical remote sensing imageries. Finally, based on analysis of these SNR estimation methods in simulated images and real images, their advantages and disadvantages are presented. Compared the typical methods with the improved methods, the latter show distinctly enhanced robustness and the estimation of the SNR is proved to be more accurate. In conclusion, when applying the methods to estimate the SNR of optical remote sensing imageries accurately and reasonably, we can get twice the result with half the effort.

Keywords  Image noise; Signal-to-noise ratio estimation; Image block; Local standard deviations; Decorrelation

1  绪论 1

1．1  信噪比的概念 1

1．2  光学遥感图像的噪声 1

1．3  研究光学遥感图像信噪比的意义 2

1．4  论文章节的安排 3

2  光学遥感图像信噪比估算的经典方法 4

2．1  方差法 4

2．2  地学统计法 4

2．3  局部均值/局部标准差法 5

2．4  空间维与光谱维去相关法 6

2．5  本章总结 8

3  光学遥感图像信噪比估算方法优化 9

3．1  去除边缘的局部均值/局部标准差法 9

3．2  计算残差的局部均值/局部标准差法 9

3．3  去除边缘的空间维去相关法 10

3．4  本章总结 12

4  实验结果与分析 13

4．1  对模拟图像信噪比估算结果 13