Dual Tree Complex Wavelet Transform for Adaptive Interferogram Residual Reduction

A novel scheme for interferogram filtering is presented in this paper. The main concern of the proposed scheme is to lower the residues count mean while preserving the location and jump height of the lines of phase discontinuity. The real interferogram is converted to complex form by using wrapped phase values as an argument of complex exponentially, placing the data on the unit circle on the complex plane and thus removing the jump discontinuity. Dual Tree Complex Wavelet Transform (DT-CWT) is then used to perform 2-D multiresolution discrete wavelet transform for complex interferogram. For each sub-band, a simple bivariate shrinkage rule is applied to the coefficients and its parents, taking into account the statistical dependencies among wavelet coefficients. After thresholding, the coefficients are retransformed using synthesis filter bank. The results are compared to both of Daubechies’ real orthogonal max flat filter and pivot median filter. Results show that the proposed scheme surplus other techniques in terms of reducing residuals count and unwrapping accuracy.