The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kaedah pembahagian baharu untuk imej Radar Apertur Sintetik (SAR) menggunakan tenaga gelombang pencong telah dipersembahkan. Kecondongan ialah terkumpul tertib ketiga yang mengukur tekstur tempatan di sepanjang kontur aktif berasaskan rantau. Tidak lineariti dalam ketidakhomogenan intensiti sering berlaku dalam imej SAR disebabkan oleh bunyi bintik. Dalam makalah ini, kami mencadangkan model kontur aktif berasaskan rantau yang mampu menggunakan maklumat keamatan di kawasan setempat dan untuk mengatasi bunyi bintik-bintik dan ketidakhomogenan intensiti tak linear imej SAR. Kami menggunakan taburan tenaga pekali wavelet untuk menganalisis tekstur imej SAR dalam setiap sub-jalur. Tenaga yang sesuai yang dipanggil tenaga wavelet pencongan ditakrifkan dari segi kontur dan berfungsi supaya, kawasan dan antara mukanya akan dimodelkan oleh fungsi set tahap. Perhubungan fungsian telah dikira pada set tahap ini dari segi terkumpul tertib ketiga, daripada mana pengurangan tenaga diperolehi. Meminimumkan fungsi yang dikira memperoleh pembahagian optimum berdasarkan definisi tekstur. Keputusan algoritma yang dilaksanakan pada imej ujian daripada imej Radarsat SAR kawasan pertanian dan bandar menunjukkan prestasi yang wajar bagi kaedah yang dicadangkan.
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Salinan
Gholamreza AKBARIZADEH, Gholam Ali REZAI-RAD, Shahriar BARADARAN SHOKOUHI, "A New Region-Based Active Contour Model with Skewness Wavelet Energy for Segmentation of SAR Images" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 7, pp. 1690-1699, July 2010, doi: 10.1587/transinf.E93.D.1690.
Abstract: A new method of segmentation for Synthetic Aperture Radar (SAR) images using the skewness wavelet energy has been presented. The skewness is the third order cumulant which measures the local texture along the region-based active contour. Nonlinearity in intensity inhomogeneities often occur in SAR images due to the speckle noise. In this paper we propose a region-based active contour model that is able to use the intensity information in local regions and to cope with the speckle noise and nonlinear intensity inhomogeneity of SAR images. We use a wavelet coefficients energy distribution to analyze the SAR image texture in each sub-band. A fitting energy called skewness wavelet energy is defined in terms of a contour and a functional so that, the regions and their interfaces will be modeled by level set functions. A functional relationship has been calculated on these level sets in terms of the third order cumulant, from which an energy minimization is derived. Minimizing the calculated functions derives the optimal segmentation based on the texture definitions. The results of the implemented algorithm on the test images from the Radarsat SAR images of agricultural and urban regions show a desirable performance of the proposed method.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.1690/_p
Salinan
@ARTICLE{e93-d_7_1690,
author={Gholamreza AKBARIZADEH, Gholam Ali REZAI-RAD, Shahriar BARADARAN SHOKOUHI, },
journal={IEICE TRANSACTIONS on Information},
title={A New Region-Based Active Contour Model with Skewness Wavelet Energy for Segmentation of SAR Images},
year={2010},
volume={E93-D},
number={7},
pages={1690-1699},
abstract={A new method of segmentation for Synthetic Aperture Radar (SAR) images using the skewness wavelet energy has been presented. The skewness is the third order cumulant which measures the local texture along the region-based active contour. Nonlinearity in intensity inhomogeneities often occur in SAR images due to the speckle noise. In this paper we propose a region-based active contour model that is able to use the intensity information in local regions and to cope with the speckle noise and nonlinear intensity inhomogeneity of SAR images. We use a wavelet coefficients energy distribution to analyze the SAR image texture in each sub-band. A fitting energy called skewness wavelet energy is defined in terms of a contour and a functional so that, the regions and their interfaces will be modeled by level set functions. A functional relationship has been calculated on these level sets in terms of the third order cumulant, from which an energy minimization is derived. Minimizing the calculated functions derives the optimal segmentation based on the texture definitions. The results of the implemented algorithm on the test images from the Radarsat SAR images of agricultural and urban regions show a desirable performance of the proposed method.},
keywords={},
doi={10.1587/transinf.E93.D.1690},
ISSN={1745-1361},
month={July},}
Salinan
TY - JOUR
TI - A New Region-Based Active Contour Model with Skewness Wavelet Energy for Segmentation of SAR Images
T2 - IEICE TRANSACTIONS on Information
SP - 1690
EP - 1699
AU - Gholamreza AKBARIZADEH
AU - Gholam Ali REZAI-RAD
AU - Shahriar BARADARAN SHOKOUHI
PY - 2010
DO - 10.1587/transinf.E93.D.1690
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2010
AB - A new method of segmentation for Synthetic Aperture Radar (SAR) images using the skewness wavelet energy has been presented. The skewness is the third order cumulant which measures the local texture along the region-based active contour. Nonlinearity in intensity inhomogeneities often occur in SAR images due to the speckle noise. In this paper we propose a region-based active contour model that is able to use the intensity information in local regions and to cope with the speckle noise and nonlinear intensity inhomogeneity of SAR images. We use a wavelet coefficients energy distribution to analyze the SAR image texture in each sub-band. A fitting energy called skewness wavelet energy is defined in terms of a contour and a functional so that, the regions and their interfaces will be modeled by level set functions. A functional relationship has been calculated on these level sets in terms of the third order cumulant, from which an energy minimization is derived. Minimizing the calculated functions derives the optimal segmentation based on the texture definitions. The results of the implemented algorithm on the test images from the Radarsat SAR images of agricultural and urban regions show a desirable performance of the proposed method.
ER -