دوره 18، شماره 1 - ( 3-1400 )
جلد 18 شماره 1 صفحات 87-102 |
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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
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
گروه مهندسی سیستم و مکاترونیک دانشکده علوم و فنون نوین، دانشگاه تهران
چکیده: (2382 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.
واژه‌های کلیدی: انتخاب ویژگی، طبقه‌بندی تصویر، ماشین بردار پشتیبان، بهینه‌سازی، الگوریتم جستجوی گرانشی دودویی، پلاریمتری رادار
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
دریافت: 1397/6/12 | پذیرش: 1399/12/6 | انتشار: 1400/3/1 | انتشار الکترونیک: 1400/3/1
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