离散双正交小波变换 DBWT
Orthogonal wavelet transform is also an efficient image merging method. Its special characteristics about localizing the time-frequency can distill information form signals and analyze the image by flexing and moving.
正交小波变换也是目前流行的一种有效的镶嵌(拼接)方法,它特有的时频局部化功能有效地从信号中提取信息,并通过伸缩和平移等运算功能对图像进行多尺度细化分析。
参考来源 - 基于小波变换的图像镶嵌算法The core of decompression is wavelet kernel using by ADV611, that is, two-dimensional bi-orthogonal wavelet transform.
解压缩的核心是ADV611所用的小波核，即二维正交小波变换。
参考来源 - 基于小波算法的视频软解压播放系统的研究方案·2,447,543篇论文数据，部分数据来源于NoteExpress
特别是对阈值去噪方法，提出了一种基于正交小波变换和自适应学习算法的噪声抑制方法。
Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here.
在以上小波分析理论的基础上进一步讨论了二维正交小波变换和离散图像的小波变换实现。
Based on mentioned-above wavelet analysis theories, two-dimension biorthogonal wavelet and the implementation of wavelet transform on discrete images have been discussed.
构造了正交小波变换矩阵，分析了平稳模型和非平稳模型下正交小波变换的残余相关特性。
Orthogonal wavelet transform (OWT) matrix is constructed and the residual correlation property of OWT is analyzed under the stationary and nonstationary models.
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