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In processing of ocean-bottom-node (OBN) data, vertical particle velocity (Vz) data, recorded by geophones, and pressure (P) data, recorded by hydrophones, can be used conjunctively for up-and down-going wavefield separation. However, shear noise attenuation needs to occur in the Vz data before it can be matched to the P data. The noise attenuation and the matching can be achieved in one step by local attribute matching in the dualtree complex wavelet transform (DTCWT) domain. Shear noise on Vz data can be characterized as low frequency and composed of a wide range of local dips. Conventional DTCWT does recursive band analysis only in the LL-band (low-f and low-k band). Therefore, shear noise with k in the higher half-band cannot be wellresolved in the frequency domain due to the poor frequency resolution in the LH band. As a result, the attenuation of high-k shear noise can be inadequate in conventional DTCWT domain. This paper proposes a new scheme to do 2D complex wavelet transformations that can provide adaptive angular-resolving capability for each analysis stage and thus solve the problem of poor high-k shear noise suppression with conventional 2D DTCWT.