*4.3. Evaluation Metrics*

The objective of phase filtering is to suppress noise and preserve interferometric phase details as much as possible. Therefore, the precision of a filtering approach is evaluated by considering both the denoising ability and the phase detail preservation ability. Moreover, the computational complexity is also an important problem for phase filtering, so the evaluation of computational efficiency is essential. In order to compare the performance of filtering methods more intuitively, we adopted two evaluation methods based on the image and data, namely, qualitative evaluation and quantitative evaluation. Qualitative evaluation is implemented directly by the naked eye, which is highly subjective and the evaluation results are not entirely desirable. In contrast, quantitative evaluation has a certain theoretical basis, so the evaluation results are highly reliable. In this paper, the meansquare error (MSE) [49] representing the difference between the filtered interferometric phase and the corresponding ground truth, the number of residues (NOR) [50] used to reflect the denoising ability of a filtering method, the mean structural similarity index (MSSIM) [51] reflecting the phase detail feature preservation ability of a filtering method, and running time (T) were adopted to assess the experiments on the simulated data. In view of lacking the ground truth of the real InSAR data, the no-reference metric Q [52] is a quantitative assessment index of balancing between phase detail preservation and denoising, and the higher this is, the more powerful the phase detail preservation capacity.
