Complex-Valued Region-Based-Coupling Image Clustering Neural Networks for Interferometric Radar Image Processing
Summary :
Complex-valued region-based-coupling image clustering (continuous soft segmentation) neural networks are proposed for interferometric radar image processing. They deal with the amplitude and phase information of radar data as a combined complex-amplitude image. Thereby, not only the reflectance but also the distance (optical length) are consistently taken into account for the clustering process. A continuous complex-valued label is employed whose structure is the same as that of input raw data and estimation image. Experiments demonstrate successfully the clustering operations for interferometric synthetic aperture radar (InSAR) images. The method is applicable also to future radar systems for image acquisition in, e.g., invisible fire smoke places and intelligent transportation systems by generating a processed image more recognizable by human and automatic recognition machine.
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- IEICE TRANSACTIONS on Electronics Vol.E84-C No.12 pp.1932-1938
- Publication Date
- 2001/12/01
- Publicized
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- Type of Manuscript
- Special Section PAPER (Special Issue on New Technologies in Signal Processing for Electromagnetic-wave Sensing and Imaging)
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Akira HIROSE, Motoi MINAMI, "Complex-Valued Region-Based-Coupling Image Clustering Neural Networks for Interferometric Radar Image Processing" in IEICE TRANSACTIONS on Electronics,
vol. E84-C, no. 12, pp. 1932-1938, December 2001, doi: .
Abstract: Complex-valued region-based-coupling image clustering (continuous soft segmentation) neural networks are proposed for interferometric radar image processing. They deal with the amplitude and phase information of radar data as a combined complex-amplitude image. Thereby, not only the reflectance but also the distance (optical length) are consistently taken into account for the clustering process. A continuous complex-valued label is employed whose structure is the same as that of input raw data and estimation image. Experiments demonstrate successfully the clustering operations for interferometric synthetic aperture radar (InSAR) images. The method is applicable also to future radar systems for image acquisition in, e.g., invisible fire smoke places and intelligent transportation systems by generating a processed image more recognizable by human and automatic recognition machine.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e84-c_12_1932/_p
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@ARTICLE{e84-c_12_1932,
author={Akira HIROSE, Motoi MINAMI, },
journal={IEICE TRANSACTIONS on Electronics},
title={Complex-Valued Region-Based-Coupling Image Clustering Neural Networks for Interferometric Radar Image Processing},
year={2001},
volume={E84-C},
number={12},
pages={1932-1938},
abstract={Complex-valued region-based-coupling image clustering (continuous soft segmentation) neural networks are proposed for interferometric radar image processing. They deal with the amplitude and phase information of radar data as a combined complex-amplitude image. Thereby, not only the reflectance but also the distance (optical length) are consistently taken into account for the clustering process. A continuous complex-valued label is employed whose structure is the same as that of input raw data and estimation image. Experiments demonstrate successfully the clustering operations for interferometric synthetic aperture radar (InSAR) images. The method is applicable also to future radar systems for image acquisition in, e.g., invisible fire smoke places and intelligent transportation systems by generating a processed image more recognizable by human and automatic recognition machine.},
keywords={},
doi={},
ISSN={},
month={December},}
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TY - JOUR
TI - Complex-Valued Region-Based-Coupling Image Clustering Neural Networks for Interferometric Radar Image Processing
T2 - IEICE TRANSACTIONS on Electronics
SP - 1932
EP - 1938
AU - Akira HIROSE
AU - Motoi MINAMI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E84-C
IS - 12
JA - IEICE TRANSACTIONS on Electronics
Y1 - December 2001
AB - Complex-valued region-based-coupling image clustering (continuous soft segmentation) neural networks are proposed for interferometric radar image processing. They deal with the amplitude and phase information of radar data as a combined complex-amplitude image. Thereby, not only the reflectance but also the distance (optical length) are consistently taken into account for the clustering process. A continuous complex-valued label is employed whose structure is the same as that of input raw data and estimation image. Experiments demonstrate successfully the clustering operations for interferometric synthetic aperture radar (InSAR) images. The method is applicable also to future radar systems for image acquisition in, e.g., invisible fire smoke places and intelligent transportation systems by generating a processed image more recognizable by human and automatic recognition machine.
ER -
English
