A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process

Andriyan Bayu SUKSMONO; Akira HIROSE

doi:10.1093/ietcom/e88-b.1.364

A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process

Andriyan Bayu SUKSMONO, Akira HIROSE

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Two-dimensional phase unwrapping (PU) process usually causes a noise-induced distortion in the geographical information of a wrapped phase image obtained by, for example, interferometric synthetic aperture radar (InSAR). This paper presents a novel method to reduce the phase-unwrapping distortion by being based on two-dimensional fractional Brownian motion (fBm) theory. The method incorporates fractal geometry estimation with conventional global-transform PU. For the spatial-frequency spectrum of an observed phase image, we estimate the fractal dimension by assuming an almost constant dimension over the image. Then, according to the estimation, we compensate the distorted spectrum of the tentatively computed global PU result. We obtain a better topographical map as the inverse Fourier transform of the compensated spectrum. It is demonstrated that the proposed method increases the signal-to-noise ratio of PU results for simulated data with various noise levels. Evaluations on an actual InSAR phase image also show that the method significantly improves the quality of the conventional global-transform PU result, in particular in its fine structure.

Publication: IEICE TRANSACTIONS on Communications Vol.E88-B No.1 pp.364-371

Publication Date: 2005/01/01

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DOI: 10.1093/ietcom/e88-b.1.364

Type of Manuscript: PAPER

Category: Sensing

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Andriyan Bayu SUKSMONO, Akira HIROSE, "A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process" in IEICE TRANSACTIONS on Communications, vol. E88-B, no. 1, pp. 364-371, January 2005, doi: 10.1093/ietcom/e88-b.1.364.
Abstract: Two-dimensional phase unwrapping (PU) process usually causes a noise-induced distortion in the geographical information of a wrapped phase image obtained by, for example, interferometric synthetic aperture radar (InSAR). This paper presents a novel method to reduce the phase-unwrapping distortion by being based on two-dimensional fractional Brownian motion (fBm) theory. The method incorporates fractal geometry estimation with conventional global-transform PU. For the spatial-frequency spectrum of an observed phase image, we estimate the fractal dimension by assuming an almost constant dimension over the image. Then, according to the estimation, we compensate the distorted spectrum of the tentatively computed global PU result. We obtain a better topographical map as the inverse Fourier transform of the compensated spectrum. It is demonstrated that the proposed method increases the signal-to-noise ratio of PU results for simulated data with various noise levels. Evaluations on an actual InSAR phase image also show that the method significantly improves the quality of the conventional global-transform PU result, in particular in its fine structure.
URL: https://globals.ieice.org/en_transactions/communications/10.1093/ietcom/e88-b.1.364/_p

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@ARTICLE{e88-b_1_364,
author={Andriyan Bayu SUKSMONO, Akira HIROSE, },
journal={IEICE TRANSACTIONS on Communications},
title={A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process},
year={2005},
volume={E88-B},
number={1},
pages={364-371},
abstract={Two-dimensional phase unwrapping (PU) process usually causes a noise-induced distortion in the geographical information of a wrapped phase image obtained by, for example, interferometric synthetic aperture radar (InSAR). This paper presents a novel method to reduce the phase-unwrapping distortion by being based on two-dimensional fractional Brownian motion (fBm) theory. The method incorporates fractal geometry estimation with conventional global-transform PU. For the spatial-frequency spectrum of an observed phase image, we estimate the fractal dimension by assuming an almost constant dimension over the image. Then, according to the estimation, we compensate the distorted spectrum of the tentatively computed global PU result. We obtain a better topographical map as the inverse Fourier transform of the compensated spectrum. It is demonstrated that the proposed method increases the signal-to-noise ratio of PU results for simulated data with various noise levels. Evaluations on an actual InSAR phase image also show that the method significantly improves the quality of the conventional global-transform PU result, in particular in its fine structure.},
keywords={},
doi={10.1093/ietcom/e88-b.1.364},
ISSN={},
month={January},}

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TY - JOUR
TI - A Fractal Estimation Method to Reduce the Distortion in Phase Unwrapping Process
T2 - IEICE TRANSACTIONS on Communications
SP - 364
EP - 371
AU - Andriyan Bayu SUKSMONO
AU - Akira HIROSE
PY - 2005
DO - 10.1093/ietcom/e88-b.1.364
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E88-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2005
AB - Two-dimensional phase unwrapping (PU) process usually causes a noise-induced distortion in the geographical information of a wrapped phase image obtained by, for example, interferometric synthetic aperture radar (InSAR). This paper presents a novel method to reduce the phase-unwrapping distortion by being based on two-dimensional fractional Brownian motion (fBm) theory. The method incorporates fractal geometry estimation with conventional global-transform PU. For the spatial-frequency spectrum of an observed phase image, we estimate the fractal dimension by assuming an almost constant dimension over the image. Then, according to the estimation, we compensate the distorted spectrum of the tentatively computed global PU result. We obtain a better topographical map as the inverse Fourier transform of the compensated spectrum. It is demonstrated that the proposed method increases the signal-to-noise ratio of PU results for simulated data with various noise levels. Evaluations on an actual InSAR phase image also show that the method significantly improves the quality of the conventional global-transform PU result, in particular in its fine structure.
ER -