Ground-penetrating radar (GPR) is a popular technique to detect buried objects such as landmines. It is well known that the target detection process in GPR is highly affected by clutter since targets are buried at shallow depths. Thus, design a target detection scheme with less false alarm rate is the ultimate goal of a GPR system. Therefore, various subspace or multiscale methods has been proposed for clutter removal in GPR images. In this paper, multiscale directional bilateral filter (MDBF) is integrated in GPR scheme. Due to its range and spatial parameters determined in order to enhance a predefined metric appropriate to the desired application, MDBF can provide a more flexible decomposition unlike the other multiresolution approaches with constants kernels. This property enables the input images to be decomposed into the directional detail subbands with different geometrical structures. Then, the informative subbands for target are preserved and the inverse MDBF is applied to reconstruct noise-free image. The results show the superiority of our algorithm compared to other multiresolution based methods proposed in the literature.