  Nowadays, interferometric synthetic aperture radar (InSAR) has been a
powerful tool in remote sensing by enhancing the information acquisition.
During the InSAR processing, phase denoising of interferogram is a mandatory
step for topography mapping and deformation monitoring. Over the last three
decades, a large number of effective algorithms have been developed to do
efforts on this topic. In this paper, we give a comprehensive overview of InSAR
phase denoising methods, classifying the established and emerging algorithms
into four main categories. The first two parts refer to the categories of
traditional local filters and transformed-domain filters, respectively. The
third part focuses on the category of nonlocal (NL) filters, considering their
outstanding performances. Latter, some advanced methods based on new concept of
signal processing are also introduced to show their potentials in this field.
Moreover, several popular phase denoising methods are illustrated and compared
by performing the numerical experiments using both simulated and measured data.
The purpose of this paper is intended to provide necessary guideline and
inspiration to related researchers by promoting the architecture development of
InSAR signal processing.
