欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
传统的小波变换方法用于信号的逼近、重构和消噪，通常会引起信号失真，例如在信号奇异点处的Gibbs现象，这是由于小波基函数的连续特性所引起的．该文提出一种新的尺度不变V变换（SIVT），可用于信号重构和消噪，并能有效消除信号逼近过程中的Gibbs现象．V系统是Haar小波基函数的扩展，并且是一种不变集上的多小波．信号消噪的困难点在于奇异点处的局部信号重构．该文通过对信号奇异点的分析，创新地提出采样信号局部尺度变换结合正交变换的方法（称为尺度不变V变换）进行信号消噪重构．实验结果表明该文方法消噪重构的信号比基于小波变换重构的信号有着更好的效果和更高的信噪比值．尺度不变V变换的理论表明了这种新的技术框架在某些信号重构问题上比小波变换方法更具优势．
英文摘要：
Approximation, reconstruction and denoising of signals with traditional wavelet transform sometimes exhibit visual artifacts, for example, Gibbs phenomena in the vicinity of discontinuities, which are caused by the continuous property of the wavelet basis. We present a novel method for signal de-noising using Scale-Invariant V-Transform （SIVT）. The V-system is the generalization of the well-known Haar wavelet basis function and it is multi-wavelets in invariant set. An aporia of signal denoising is that the local signal reconstruction at the singular points. Based on the analysis for the signal singular points, combining local signal resampling and orthogonal transform, a novel technical framework--SIVT has been proposed for signal de-noising. The test results reveal the SIVT reconstructions exhibit higher visual quality and numerical measurement of SNR than wavelet-based reconstructions. Existing theory of SIVT suggests that these new approaches can perform significantly better than wavelet methods in certain signal reconstruction problems.
同期刊论文项目
同项目期刊论文
期刊信息
位置：