Singularity-Spreading Phase Unwrapping

How to process phase singular points (SPs), or residues, is a difficult problem in a 2-D phase-unwrapping process to generate digital elevation maps (DEMs). Although the minimum-cost network-flow method is an effective and widely used technique, some problems still remain. That is, the method often generates spikes in high SP-density areas and long clifflike artifacts for isolated SPs. It also takes a long time to unwrap phase data that contain many SPs. In this paper, we propose a new unwrapping method, namely, singularity-spreading phase unwrapping (SSPU), which solves these problems. In this method, we spread the singularity at SPs around to make the closely located positive and negative SPs combine gently with each other or make the isolated SPs fade away. Experiments demonstrate that the spreading process compensates the distortion in phase values in the vicinities of SPs appropriately for landscape reconstruction. The SSPU generates high-quality DEMs with smaller calculation costs than the conventional method. Besides the simple SSPU, we also present weighted SSPU where we utilize amplitude information to improve the performance further. In addition, we discuss the relationship between landscape characteristics and SSPU performance.

[1]  Mario Costantini,et al.  A novel phase unwrapping method based on network programming , 1998, IEEE Trans. Geosci. Remote. Sens..

[2]  Akira Hirose,et al.  Progressive Transform-Based Phase Unwrapping Utilizing a Recursive Structure , 2006, IEICE Trans. Commun..

[3]  A. Reigber,et al.  Phase unwrapping by fusion of local and global methods , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.

[4]  Akira Hirose,et al.  A Radar System with Phase-Sensitive Millimetric Wave Circuitry and Complex-Amplitude Neural Processing , 1998 .

[5]  Akira Hirose,et al.  A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process , 2005, IEICE Trans. Commun..

[6]  Henri Maître,et al.  Improving phase unwrapping techniques by the use of local frequency estimates , 1998, IEEE Trans. Geosci. Remote. Sens..

[7]  Paul W. Fieguth,et al.  Probabilistic cost functions for network flow phase unwrapping , 2000, IEEE Trans. Geosci. Remote. Sens..

[8]  Akira Hirose,et al.  Adaptive noise reduction of InSAR images based on a complex-valued MRF model and its application t o phase unwrapping problem , 2002, IEEE Trans. Geosci. Remote. Sens..

[9]  Paul Fieguth,et al.  Multiresolution network flow phase unwrapping , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).