基于改进经验模式分解的遥感图像融合

发布时间：2018-05-17 00:22

本文选题：遥感图像融合 + IHS变换　；参考：《浙江工商大学》2017年硕士论文

【摘要】：遥感图像融合就是通过一定的算法去除两幅或者多幅遥感图像的冗余信息,同时保留源图像的互补信息,并集中在同一幅新图像的过程。随着遥感技术的飞速发展,遥感图像融合技术也具有较大的提升,融合效果也有很大的改善。为了达到更好的图像融合效果,本文结合IHS变换和(?) trous小波变换,提出了一种改进二维经验模式分解的遥感图像融合算法,既保留了图像的光谱信息又提高了图像纹理细节的表现能力。本文的主要研究工作和创新点如下:1、阐述了遥感图像融合算法的研究背景与意义,指出了传统图像融合算法的优缺点,重点研究了 IHS变换和(?) trous小波变换在遥感图像预处理中的应用问题。2、对经验模式分解的各个环节进行剖析研究,给出了实现步骤,并指出了经验模式分解存在的关键问题。3、针对二维经验模式分解过程中的构造图像的上下包络曲面、筛分过程的终止条件以及快速分解算法进行了改进,本文提出了一种改进经验模式分解算法,避免了处理大型线性系统的系数矩阵、求解大型线性系统方程组的困难,减少了运算量,降低了计算复杂度,更精准地结束筛分过程,提高了分解速度。4、针对遥感图像融合,本文提出了一种基于改进经验模式分解融合算法,给出了具体的融合步骤,并进行了多组遥感图像仿真实验。从定性的主观评价到定量的客观评价分析了融合图像,不仅保留了高光谱信息,还增强了图像的空间分辨率,提高了图像的清晰度以及纹理细节的表现能力,取得较好的融合效果。
[Abstract]:Remote sensing image fusion is the process of removing redundant information from two or more remote sensing images by a certain algorithm while preserving complementary information of the source image and concentrating on the same new image. With the rapid development of remote sensing technology, remote sensing image fusion technology has been greatly improved, and the fusion effect has been greatly improved. In order to achieve better image fusion effect, combining IHS transform and trous wavelet transform, an improved 2D empirical mode decomposition algorithm for remote sensing image fusion is proposed in this paper. It not only preserves the spectral information of the image, but also improves the performance of the texture details of the image. The main research work and innovation of this paper are as follows: 1. The background and significance of remote sensing image fusion algorithm are expounded, and the advantages and disadvantages of traditional image fusion algorithm are pointed out. The application of IHS transform and trous wavelet transform in remote sensing image preprocessing is studied in detail. The key problem of empirical mode decomposition (EMD) is pointed out in this paper. In view of the upper and lower envelope surfaces of the constructed images in the process of 2D EMD, the termination conditions of the screening process and the fast decomposition algorithm are improved. In this paper, an improved empirical mode decomposition algorithm is proposed, which avoids the difficulty of dealing with the coefficient matrix of large linear systems, solves the equations of large linear systems, reduces the computational complexity, and ends the screening process more accurately. For remote sensing image fusion, an improved empirical mode decomposition and fusion algorithm is proposed, and the specific fusion steps are given, and several remote sensing image simulation experiments are carried out. The fusion image is analyzed from qualitative subjective evaluation to quantitative objective evaluation. It not only preserves hyperspectral information, but also enhances the spatial resolution of the image, improves the sharpness of the image and the expressive ability of the texture details. Good fusion effect was achieved.
【学位授予单位】：浙江工商大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP751

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