摘 要
随着网络及计算机在人们生活中的日益普及,图像、音频等多种形式的多媒体文件极大地丰富了人们的生活。同时人们对于图像的画质要求也在不断提高,于是图像处理就提到了研究的日程上来。
本文首先简要研究了近年来小波分析的发展及其在图像处理方面的应用情况,然后引入了小波变换的一些基本理论,并由此提出了小波包分析。因为小波包理论是在小波变换的基础上形成的,不同的是小波包变换能够对图像中的高频部分进行再分解,频率区分更加精细,因此更适合于图像的各种处理。最后本文系统地描述了目前常用的小波包对图像消噪和压缩的一些算法,利用Matlab的小波工具箱中的函数实现一些实验,验证了本文提出的小波包对图像消噪和压缩算法的有效性。
关键词:小波变换;小波包变换;图像消噪;图像压缩
With internet and computer used more frequently, the multimedia just like audio, video etc. enriches human’s life a lot. Meanwhile, the requirement of image quality is raising day by day .Therefore, it is necessary to do some research on image processing.
First and foremost, detailed introduction of wavelet analysis development in recent years and its application in image processing are given in this paper. Then we introduced some basic theory in wavelet transform. On this basis, we recommend the wavelet packets transform. Wavelet packets transform is formed on the basis of wavelet transform, and its peculiarity is that it can decompose the high-frequency component of the image and distinguish the frequency more exactly. So it is more suitable for image processing. Finally, this paper systematically describes the common algorithms which are used by wavelet packets in image de-noising and compression. We use Wavelet Toolbox in Matalb to carry out some experiments, and proved the efficiency of the algorithms which are used in image processing.
Keywords : wavelet transform ; wavelet packets transform ; image de-noising ;image compression