:: دوره 9، شماره 2 - ( 7-1400 ) ::
جلد 9 شماره 2 صفحات 27-1 برگشت به فهرست نسخه ها
طبقه بندی تصاویر ابرطیفی با استفاده از ادغام ویژگی های طیفی و مکانی در شبکه های عصبی پیچشی
عبید شریفی* ، بهنام اصغری بیرامی ، مهدی مختارزاده
دانشگاه صنعتی خواجه نصیرالدین طوسی
چکیده:   (2180 مشاهده)
سنجنده­ های ابرطیفی به واسطه اخذ تعداد زیادی از باندهای طیفی همواره دارای اهمیت خاصی در پایش پدیده ­های سطح زمین می ­باشند. طبقه­ بندی تصاویر ابرطیفی مهم­ترین روش پردازش داده­ های ابرطیفی می ­باشد که تا به حال تلاش­ های زیادی برای افزایش دقت آن صورت گرفته است. شبکه­ های عصبی پیچشی و ویژگی­ های مکانی در سال­ های اخیر جایگاه مهمی در بهبود دقت طبقه­ بندی تصاویر ابرطیفی داشته­ اند. در تحقیقات پیشین توجه زیادی به استفاده همزمان از قابلیت ­های روش ­های استخراج ویژگی مکانی در شبکه­ های عصبی پیچشی نشده است. به همین دلیل در مقاله حاضر یک معماری جدید از شبکه­ های عصبی پیچشی برای طبقه­ بندی تصاویر ابرطیفی معرفی شده است که به عنوان ورودی شبکه از بردار طیفی­_مکانی حاصل از ترکیبات مختلف ویژگی­ های مکانی شامل  پروفایل ­های مورفولوژی، بانک فیلترگابور و الگوی باینری محلی(LBP) با ویژگی­ های طیفی استخراج شده از روش تبدیل مولفه اصلی استفاده می ­کند. آزمایش ­های این مقاله که بر روی دو تصویر ابرطیفی حقیقی از دو منطقه کشاورزی و شهری صورت گرفته است، نشان از برتری روش پیشنهادی دارد. نتایج نهایی نشان می­ دهد که دقت کلی طبقه ­بندی با روش پیشنهادی می ­تواند در بهترین حالت  2/5 درصد از روش ­های رقیب بهتر باشد.
واژه‌های کلیدی: طبقه بندی تصاویر ابرطیفی، شبکه های عصبی پیچشی، پروفایل های مورفولوژی، بانک فیلتر گابور، الگوی باینری محلی (LBP)
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نوع مطالعه: پژوهشي | موضوع مقاله: سنجش از دور
دریافت: 1398/5/7 | پذیرش: 1398/10/8 | انتشار: 1400/7/30
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دوره 9، شماره 2 - ( 7-1400 ) برگشت به فهرست نسخه ها