Denoising performance of modified dual tree complex wavelet transform

Dual-tree complex wavelet transform (DTCWT) is a shift invariant transform with limited redundancy. Complex quadrature signals are dual channel signals obtained from the systems employing quadrature demodulation. An example of such signals is quadrature Doppler signal obtained from blood flow analysis systems. Prior to processing Doppler signals using the DTCWT, directional flow signals must be obtained and then two separate DTCWT applied, increasing the computational complexity. In order to decrease computational complexity, a modified DTCWT (MDTCWT) algorithm can be used. In this study denoising performance of MDTCWT is compared with DTCWT and conventional Discrete wavelet transform (DWT) by using simulation signals. Results demonstrate that the MDTCWT based denoising outperforms conventional discrete wavelet based denoising.