دوره 18، شماره 1 - ( 3-1400 )                   جلد 18 شماره 1 صفحات 102-87 | برگشت به فهرست نسخه ها

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rezaei Y, rezaee A, darakeh F, azarakhsh Z. Classification of polarimetric radar images based on SVM and BGSA. JSDP. 2021; 18 (1) :102-87
URL: http://jsdp.rcisp.ac.ir/article-1-895-fa.html
رضائی یاسر، رضائی علیرضا، درکه فاطمه، آذرخش زینب. طبقه‌بندی تصاویر پلاریمتری رادار مبتنی بر ماشین بردار پشتیبان و الگوریتم جستجوی گرانشی دودویی. پردازش علائم و داده‌ها. 1400; 18 (1) :102-87

URL: http://jsdp.rcisp.ac.ir/article-1-895-fa.html


گروه مهندسی سیستم و مکاترونیک دانشکده علوم و فنون نوین، دانشگاه تهران
چکیده:   (347 مشاهده)
هدف از این پژوهش ارائه یک روش بهینه بهه‌­منظور طبقه­‌بندی تصاویر رادار پلاریمتری است. روش پیشنهادی تلفیقی از ماشین بردار پشتیبان و الگوریتم بهینه­‌سازی جستجوی گرانشی دودویی است. در این راستا، ابتدا مجموعه‌­ای از ویژگی­‌های پلاریمتریک شامل مقادیر داده اصلی، ویژگی­‌های تجزیه هدف و تفکیک‌کننده‌های SAR از تصاویر استخراج می­‌شوند؛ سپس به‌منظور انتخاب ویژگی­‌های مناسب و تعیین پارامترهای بهینه برای طبقه‌­بندی‌کننده ماشین بردار پشتیبان از الگوریتم جستجوی گرانشی دودویی استفاده شده است. به‌منظور دست‌یابی به یک سامانه طبقه‌­بندی با دقت طبقه­‌بندی بالا، انتخاب مقادیر بهینه پارامترهای مدل و زیرمجموعه‌­ای از ویژگی‌های بهینه، به‌طور هم‌زمان انجام می‌­پذیرد. نتایج پیاده­‌سازی الگوریتم پیشنهادی با دو حالت، در‌نظر‌گرفتن تمام ویژگی‌­های انتخاب‌شده، و الگوریتم ژنتیک، قیاس شده که نتایج حاصل از تفکیک نواحی برای سه ناحیه مورد بررسی قرار گرفته است. تفکیک نواحی برای مناطق سانفرانسیسکو و مانیل، و تشخیص لکه نفتی سطح اقیانوس منطقه فیلیپین مورد ارزیابی قرار گرفته که به‌ترتیب با بهبود دقت کلی تقریبی 12، 7 و 5/6 درصد در قیاس با الگوریتم ژنتیک بهبود داشته است.
متن کامل [PDF 2230 kb]   (94 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: مقالات پردازش تصویر
دریافت: 1397/6/12 | پذیرش: 1399/12/6 | انتشار: 1400/3/1 | انتشار الکترونیک: 1400/3/1

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