小波包在图像处理中的应用_毕业设计.doc

小波包在图像处理中的应用 （陕西理工学院 物理与电信工程学院 通信工程专业1202班，陕西 汉中 723003） 指导教师： [摘 要]图像是人类获取和交换信息的主要来源，因此，图像处理涉及到人类生活的方方面面，而小波分析在图像处理领域应用广泛，如：图像去噪、图像压缩、图像融合、图像分割等。本文主要围绕小波分析在图像去噪和图像压缩这两个方面的应用展开论述。在对图像进行处理时，首先利用小波函数对图像进行空间分解,小波变换的空间分解遵循塔式结构，小波包的空间分解遵循小波包树形结构，再设置相应阈值进行系数筛选，最后经小波逆变换进行图像重构。图像的去噪和压缩实质上都是对小波分解后的高频系数、低频系数做相应处理，然后重构系数，达到图像去噪、压缩的效果。本文在小波变换和小波包的理论基础分析之上，利用MATLAB软件仿真实现了小波变换和小波包的图像去噪与压缩，并结合仿真结果，将两者做出了对比。 [关键字]小波包，小波变换，图像去噪，图像压缩，MATLAB。  Application of wavelet packet in image processing Liu haoyun (Grade 2012, Class 2, Major of Communication Engineering, School of Physics and Telecommunication Engineering of Shaanxi University of Technology, Hanzhong 723003, Shaanxi) Tutor: Chen Li Abstract: Image is the main source of human accessing and exchanging information. Therefore, image processing involves all aspects of human life, wavelet analysis is so widely applicated in the field of image processing, such as: image denoising, image compression, image fusion, image segmentation etc. This paper is focus on two aspects of image denoising and image compression. At first, wavelet function will get the image decomposed in image processing. According to the structure of the tower, the space decomposition of wavelet transform is done. According to the structure of wavelet packet tree, the space decomposition of wavelet packet is done. Secondly, the corresponding threshold is set. Finally, signal is reconstructed by inversing wavelet transform. The essential principal of image denoising and compression is the high frequency coefficients and low frequency coefficients which are processed after wavelet decomposition, then they are reconstructed to achieve the effect of image denoising and compression. Based on the theory of wavelet transform and wavelet packet analysis, it can be achieved that image denoising and compression on MATLAB, at the same time, the effect of image denoising and compression are compared . Key word