تطبیق تصاویر سنجش از دور با استفاده از آشکارساز SURF بهبود یافته و توصیفگر BRISK نامتغیر با جهت در محیط شبیهساز توابع تبدیل مستوی
فاطمه خلیلی
1
(
دانشکده مهندسی مکانیک، برق و کامپیوتر- واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
)
فربد رزازی
2
(
دانشکده مهندسی مکانیک، برق و کامپیوتر- واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران
)
ابوالفضل حسینی
3
(
گروه مهندسی برق- مرکز تحقیقات و توسعه فناوریهای پیشرفته صنعت برق و الکترونیک، واحد یادگار امام خمینی (ره) شهر ری، دانشگاه آزاد اسلامی، تهران، ایران
)
کلید واژه: تصاویر سنجش ازدور, فیلتر مورفولوژی, توصیفگرBRISK, الگوریتم SURF, انطباق تصاویر,
چکیده مقاله :
از جمله مشکلات موجود در انطباق تصاویر سنجش از دور این است که تصاویر توسط سنسورهای متنوع و در زمانهای مختلف و با زاویه های انحراف متنوع گرفته شدهاند. برای حل این مشکل الگوریتمهایی برای بهبود انطباق پیشنهاد شدهاند. یکی از متداولترین روشها، استفاده از الگوریتم SURF (ویژگی های مقاوم سریع) است که نسبت به تغییر مقیاس، چرخش، تغییر روشنایی و نویز تا حدودی مقاوم و به زاویه انحراف تصاویر تا حدود 45 درجه پاسخگو است. اما روی همافتادگی و نزدیکی نقاط کلیدی استخراج شده در این الگوریتم زیاد است و عملاً توزیع پذیری مکانی مناسبی از نقاط کلیدی را ارائه نمیدهد. این پژوهش به دنبال روشهایی است که نسبت به پارامترهای تابع تبدیل آفین مقاوم باشد. در مقاله حاضر از محیط شبیهساز IMAS (انطباق تصویر با شبیهساز توابع تبدیل مستوی) که توزیعپذیری مناسبی از نقاط کلیدی را پیشنهاد و به اختلاف زاویه بیشتری نسبت به SURF پاسخگوست، استفاده شده است. برای یافتن مرزها و لبههایی با وضوح بیشتر در تصویر از فیلتر مورفولوژی استفاده شده و برای آشکارسازی نقاط کلیدی، ایده جرم تصویر به کاربرده شده است که جهت اصلی نقاط ویژگی را مشخص و چرخشهای تغییر ناپذیر را توصیف میکند. در بخش توصیفگر از توصیفگر RBRISK (نقاط کلیدی دودویی مقیاس پذیر مقاوم و تغییرناپذیر در برابر دوران) که نسبت به دوران پایدار است، استفاده شده است. نتایج عملی آزمایشها نشان دهنده آن است که روش پیشنهادی در تصاویر ماهواره میزان انطباق را تا حدود 10 درصد بهبود بخشیده و از سرعت اجرای مناسبی در کاربردهای آنلاین برخوردار است.
چکیده انگلیسی :
Remote sensing images are often captured by a variety of sensors at different times and with various deviation angles. This makes the matching procedure of image pairs be a challenge. To solve this problem, some algorithms have been proposed to improve this matching. One of the most popular methods is SURF (Speedup robust features) algorithm, which is somewhat resistant to scale changes, rotation of images, brightness variation, and noise. In addition, the algorithm is suitable for the image deviation angles up to 45 degrees. However, the overlap and proximity of the extracted key points in this algorithm are high and it does not provide a suitable spatial distribution for the key points. This study is looking for a method that is resistant to the changes of affine transformation parameters. We use an IMAS (Image matching by affine simulation) simulator environment, which offers a suitable distribution of key points and can be considered as a solution to more angle differences than SURF. A morphology filter is used to find the boundaries and the edges with more clarity in the images. To reveal the key points, the images centers of mass are employed, which address the main direction of feature points and describe the invariable rotation. In addition, RBRISK (Rotation invariant binary robust invariant scalable key point) descriptor is employed in the algorithm which is temporally stable. The results of the experiments show that the proposed method improved the matching rate in satellite images by about 10% with suitable computational complexity.
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