摘要在社会快速进步的今天，图像融合技术已经在图像处理和图像的信息领域占 有着重要的地位，它的融合技术也是目前研究的重点。小波分解图像融合的基本 作用是利用小波分解技术提取图像像素级、特征以及目标内容信息，之后再利用 融合技术对原图像或者是目标场景获得更加准确、清晰、全面的图像消息。
小波分解的图像混合是在像素级的根本上开始，因此小波分解的时候系数 提取有时影响着图像混合的效果，因此对于图像配准的准确度要有严格要求，提 取分解系数的时候必须符合原图像的成像。对于图像的低频部分和高频部分的分 量采用中和的方式来改变最后融合图像的效果。对于一幅图像主要是通过小波的 分解得到的细节分量和近似分量，之后重构图像的细节分量和近似分量得到新的 融合图像，通过对比可以发现小波分解重构的图像可以消除原图像中部分噪声干 扰。对于两幅图像的融合本文主要是采用小波分解提取系数的算法来完成图像的 融合，对比另一种方法只是改变图像高频和低频的部分，这种方法更加有效和全 面。73948
该论文有图 31 幅，参考文献 22 篇。 毕业论文关键词：图像融合 小波分解 像素级
Image fusion based on Wavelet Transform
Abstract In the rapid development of society today, image fusion technology has occupied an important position in the field of image processing and image information, Its fusion technology is the focus of current research。。 The main purpose of wavelet image fusion uses wavelet decomposition technique to extract the image pixel level, features, and target information, after the re-use of the original image fusion technology or the target scene to obtain a more accurate, clear and comprehensive picture information。
Image fusion wavelet decomposition is to start at the pixel level, based on, so for the time wavelet coefficients extracted sometimes affect image fusion effect。 So for image registration accuracy have strict requirements when extracting decomposition coefficients must conform to the original image forming。 For low frequency and high frequency components of the image and take the way to change the effect of the final image fusion。 For details of the components of an image obtained by the main wavelet decomposition and approximate weight, after the reconstructed image details and approximate weight component to give a new image fusion, wavelet decomposition can be found by comparing the reconstructed image can eliminate part of the original image noise。 For the fusion of two images This article is extracted wavelet coefficients algorithm to complete the integration of image contrast is just another way to change the image of the high and low frequency part, this method is more effective and comprehensive。
Keyword：image fusion Wavelet decomposition Pixel level
目录
摘要 I
Abstract II
目录 III
图清单 IV
1 绪论 1
1。1 课题研究的意义和它的背景 1
1。3 本文主要研究的方向和结构安排 2
2 小波变换的相关知识 4
2。1 小波变换的介绍 4
2。2 多分辨率分析 基于小波分解的图像融合技术研究:http://www.youerw.com/tongxin/lunwen_84378.html