Title :
Interferometric SAR image restoration using Monte Carlo metropolis method
Author :
Suksmono, Andriyan Bayu ; Hirose, Akira
Author_Institution :
Res. Center for Adv. Sci. & Technol., Univ. of Tokyo, Japan
fDate :
2/1/2002 12:00:00 AM
Abstract :
We present a novel method of interferometric synthetic aperture radar (InSAR) image restoration. An InSAR image is modeled as a complex-valued Markov random field (CMRF). Corrupted parts, which are indicated by residues in phase data, are restored by using the Monte Carlo Metropolis (MM) method based on their uncorrupted neighbor´s CMRF parameter values. The system is implemented as a complex-valued neural network. The restoration process reduces the residue number, which is useful in the phase unwrapping process. The advantage of the method is demonstrated in the unwrapping process of an InSAR image that contains highly dense residues
Keywords :
Markov processes; Monte Carlo methods; image restoration; neural nets; radar computing; radar imaging; radiowave interferometry; synthetic aperture radar; CMRF; InSAR image; Monte Carlo Metropolis method; Monte Carlo algorithm; complex-valued Markov random field; complex-valued neural network; digital elevation map; error energy; interferometric SAR image restoration; phase data residues; phase unwrapping; radar imaging systems; stochastic model; Helium; Image restoration; Lattices; Markov random fields; Monte Carlo methods; Neural networks; Parameter estimation; Radar imaging; Signal processing algorithms; Synthetic aperture radar interferometry;
Journal_Title :
Signal Processing, IEEE Transactions on
