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ORTHOGONAL HILBERT TRANSFORM FILTER BANKS AND WAVELETS

机译:正交Hilbert变换过滤器银行和小波

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Complex wavelet transforms offer the opportunity to perform directional and coherent processing based on the local magnitude and phase of signals and images. Although denoising, segmentation, and image enhancement are significantly improved using complex wavelets, the redundancy of most current transforms hinders their application in compression and related problems. In this paper we introduce a new orthonormal complex wavelet transform with no redundancy for both real- and complex-valued signals. The transform's filterbank features a real lowpass filter and two complex highpass filters arranged in a critically sampled, three-band structure. Placing symmetry and orthogonality constraints on these filters, we find that each high-pass filter can be factored into a real highpass filter followed by an approximate Hilbert transform filter.
机译:复杂小波变换提供了基于信号和图像的局部幅度和相位进行定向和相干处理的机会。虽然使用复杂的小波显着改善了去噪,分割和图像增强,但大多数电流的冗余妨碍了它们在压缩和相关问题中的应用。在本文中,我们介绍了一种新的正式复杂小波变换,对实际和复数值的信号没有冗余。 Transform的FilterBank具有真正的低通滤波器和两个复合高通滤波器,布置在批判性的三带结构中。在这些过滤器上放置对称性和正交性约束,我们发现每个高通滤波器可以在真正的高通滤波器中进行,然后是近似的Hilbert变换过滤器。

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