Title :
Phase retrieval in SAR interferograms using diffusion and inpainting
Author :
Borzì, A. ; Di Bisceglie, M. ; Galdi, C. ; Pallotta, L. ; Ullo, S.L.
Author_Institution :
Eng. Dept., Univ. of Sannio, Benevento, Italy
Abstract :
A high-contrast inpainting scheme based on the Complex Ginzburg-Landau equation recently applied successfully to image restoration is applied to SAR interferograms to improve their quality and therefore final quality of Digital Elevation Models (DEMs). The new technique attempts to recover the phase values in low coherence regions through diffusion and inpainting. After phase unwrapping low coherence regions are masked and discarded and a Complex Ginzburg-Landau (CGL) inpainting scheme is applied to regions where phase values are missing. We demonstrate that the residues reduce and the proposed algorithm leads to a higher Signal-to-Noise Ratio (SNR) if compared with MCF algorithm. The restoration technique has been applied to ERS-1 and ERS-2 data sets acquired on July 1995. Results appear to be very promising: the proposed algorithm provides good performances especially in presence of strong noise level and low coherence areas with relatively small dimensions.
Keywords :
Ginzburg-Landau theory; digital elevation models; image restoration; radar imaging; radar interferometry; synthetic aperture radar; MCF algorithm; SAR interferogram; complex Ginzburg-Landau equation; diffusion; digital elevation model; high-contrast inpainting; image restoration; low coherence region; phase retrieval; phase unwrapping; phase value; signal-to-noise ratio; Coherence; Correlation; Equations; Image restoration; Mathematical model; Pixel; Signal to noise ratio; Synthetic aperture radar (SAR); diffusion processes; image restoration; interferometry; phase noise;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4244-9565-8
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2010.5652201