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درویش نژاد, محسن, سبط, محمدعلی. (1401). انتخاب ویژگیهای پلارمیتری استخراج شده از تصاویر PolSAR برمبنای اطلاعات متقابل ویژگیها به منظور طبقه بندی پوششی سطح زمین در تصاویر استخراج شده از رادار دهانه مصنوعی. پدافند الکترونیکی و سایبری, 10(1), 35-55.
محسن درویش نژاد; محمدعلی سبط. "انتخاب ویژگیهای پلارمیتری استخراج شده از تصاویر PolSAR برمبنای اطلاعات متقابل ویژگیها به منظور طبقه بندی پوششی سطح زمین در تصاویر استخراج شده از رادار دهانه مصنوعی". پدافند الکترونیکی و سایبری, 10, 1, 1401, 35-55.
درویش نژاد, محسن, سبط, محمدعلی. (1401). 'انتخاب ویژگیهای پلارمیتری استخراج شده از تصاویر PolSAR برمبنای اطلاعات متقابل ویژگیها به منظور طبقه بندی پوششی سطح زمین در تصاویر استخراج شده از رادار دهانه مصنوعی', پدافند الکترونیکی و سایبری, 10(1), pp. 35-55.
درویش نژاد, محسن, سبط, محمدعلی. انتخاب ویژگیهای پلارمیتری استخراج شده از تصاویر PolSAR برمبنای اطلاعات متقابل ویژگیها به منظور طبقه بندی پوششی سطح زمین در تصاویر استخراج شده از رادار دهانه مصنوعی. پدافند الکترونیکی و سایبری, 1401; 10(1): 35-55.

انتخاب ویژگیهای پلارمیتری استخراج شده از تصاویر PolSAR برمبنای اطلاعات متقابل ویژگیها به منظور طبقه بندی پوششی سطح زمین در تصاویر استخراج شده از رادار دهانه مصنوعی

رادار
مقاله 7، دوره 10، شماره 1 - شماره پیاپی 27، تیر 1401، صفحه 35-55    اصل مقاله (1.74 M)
نوع مقاله: مقاله پژوهشی
نویسندگان
محسن درویش نژاد* 1؛ محمدعلی سبط2
1دانشجوی دکترا، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران
2دانشیار، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران
تاریخ دریافت: 24 فروردین 1401،  تاریخ بازنگری: 16 مرداد 1401،  تاریخ پذیرش: 02 شهریور 1401 
چکیده
درسالیان اخیر، طبقه‌بندی پوششی سطح زمین به عنوان یکی از مهمترین کاربردهای تصاویر پلاریمتری استخراج شده از رادار دهانه مجازی عنوان شده است. داده‌های پلاریمتری راداری ذاتا دارای ویژگی‌های مناسبی برای طبقه‌بندی اهداف مختلف سطح زمین می‌باشند. لذا به منظور استفاده بالا و مناسب از پتانسیل بالای اطلاعاتی از این دادگان می‌توانیم ویژگی‌های متعددی از آنها استخراج نماییم. لذا استخراج ویژگی از این دادگان گام مهمی در طبقه‌بندی اهداف سطح زمین می‌باشد. در این مقاله، هدف استخراج و انتخاب ویژگی از تصاویر پلاریمتری رادار دهانه مصنوعی به شکلی است که نرخ طبقه‌بندی اهداف موجود در سطح زمین بهبود پیدا کند. در این مقاله، چهار گام اساسی برای بهبود دقت طبقه‌بندی اتخاذ شده است:1-استخراج ویژگی پلاریمتری راداری در قالب سه گروه ویژگی بنام‌های: ویژگی‌های اصلی، ویژگی‌های تجزیه هدف و تفکیک کننده‌های رادار دهانه مصنوعی.2-طبقه‌بندی اولیه دادگان با استفاده از ویژگی‌های استخراج شده.3-رتبه-بندی ویژگی‌ها بر اساس اطلاعات متقابل بین ویژگی‌ها و نقشه طبقه‌بندی اولیه بدست آمده در مرحله دوم.4-بدست آوردن ویژگی‌های بهینه با استفاده از روش‌های پیشنهادی و طبقه‌بندی نهایی. در روش‌ پیشنهادی از طبقه‌بند ماشین بردار پشتیبان به منظور طبقه‌بندی دادگان استفاده خواهد شد و ویژگی‌های بهینه به نحوی که نرخ طبقه‌بندی افزایش پیدا کند، انتخاب خواهند شد. نتایج حاصله بر روی تصویر راداری منطقه Flevoland حاکی از افزایش دقت طبقه‌بندی روش پیشنهادی نسبت به سایر روش‌های مورد استفاده در این تحقیق است.
کلیدواژه‌ها
طبقه‌بندی؛ رادار دهانه مصنوعی؛ تصاویر پلارمتری؛ انتخاب ویژگی
عنوان مقاله [English]
Feature Selection Method Based on Mutual Information for Polarimetric Synthetic Aperture Radar (PolSAR) Image Classification
نویسندگان [English]
Mohsen Darvishnezhad1؛ ُMohammad Ali Sebt2
1PhD student, K.N.Toosi University of Tech., Tehran, Iran
2Associate Professor, K.N.Toosi University of Tech., Tehran, Iran
چکیده [English]
In recent years, Polarimetric Synthetic Aperture Radar (PolSAR) image classification has been cited as one of the most important applications of images classification. Therefore, in order to achieve the best result of PolSAR image classification in this article, a new feature selection method will be proposed based on mutual information theory. In the proposed method, the features that are extracted from PolSAR images will be used to obtain an initial class map. Then, each feature will be ranked based on mutual information. In the next step, the best features will be selected by using the proposed method accurately. The results that are obtained on the real PolSAR image of the Flevoland area prove an increase in the classification accuracy of the proposed method compared with other methods that are used in this research.
کلیدواژه‌ها [English]
Classification, PolSAR, Feature Selection, Synthetic Aperture Radar
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