The Undecimated Dual Tree Complex Wavelet Transform and its application to bivariate image denoising using a Cauchy model
The Undecimated Dual Tree Complex Wavelet Transform and its application to bivariate image denoising using a Cauchy model
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DOI：
10.1109/icip.2012.6467082
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发表时间：
2012-12
期刊：
影响因子：
--
通讯作者：
P. Hill;A. Achim;D. Bull
中科院分区：
文献类型：
--
作者：
P. Hill;A. Achim;D. Bull
介绍了未抽取双树复小波变换（UDTCWT）及其在图像去噪中的应用。 UDT-CWT 使用为未抽取离散小波变换 (UDWT) 开发的滤波器上采样和去除下采样的方法扩展了传统的 DT-CWT。 UDTCWT 在所有子带中的共置复系数之间产生一对一的关系，并提供改进的较低尺度子带定位以及改进的方向选择性（与 UDWT 相比）。 UDT-CWT 的这些特性已在所提出的双变量收缩去噪算法中得到利用，并在图像去噪的应用中给出了定量改进。
The Undecimated Dual Tree Complex Wavelet Transform (UDTCWT) is introduced together with its application to image denoising. The UDT-CWT extends the traditional DT-CWT using the methods of filter upsampling and the removal of downsampling developed for the Undecimated Discrete Wavelet Transform (UDWT). The UDTCWT results in a one-to-one relationship between co-located complex coefficients in all subbands and offers improved lower scale subband localisation together with improved directional selectivity (compared to the UDWT). These properties of the UDT-CWT have been exploited in the presented bivariate shrinkage denoising algorithm and gives quantitative improvements in the application to the denoising of images.