کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529784 869708 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Gradient-based subspace phase correlation for fast and effective image alignment
ترجمه فارسی عنوان
همبستگی فازی زیر فاز مبتنی بر گرادینت برای هماهنگ سازی تصویر سریع و موثر
کلمات کلیدی
ثبت نام تصویر، تراز کردن زیر پیکسل، همبستگی فازی، شرایط تداخل، طرح فضایی، تبدیل فوریه، برآورد حرکت، الگوریتم سریع
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• To prove the efficacy of subspace phase correlation in estimating 2D image offsets.
• To prove more robust results yielded from subspace approach under zero-mean noise.
• To prove our method robust to non-zero-mean noise caused by non-overlapped regions.
• To prove higher peaks yielded by our method for robustness with reduced complexity.
• To validate the effectiveness with various synthetic data and noisy MRI images.

Phase correlation is a well-established frequency domain method to estimate rigid 2-D translational motion between pairs of images. However, it suffers from interference terms such as noise and non-overlapped regions. In this paper, a novel variant of the phase correlation approach is proposed, in which 2-D translation is estimated by projection-based subspace phase correlation (SPC). Conventional wisdom has suggested that such an approach can only amount to a compromise solution between accuracy and efficiency. In this work, however, we prove that the original SPC and the further introduced gradient-based SPC can provide robust solution to zero-mean and non-zero-mean noise, and the latter is also used to model the interference term of non-overlapped regions. Comprehensive results from synthetic data and MRI images have fully validated our methodology. Due to its substantially lower computational complexity, the proposed method offers additional advantages in terms of efficiency and can lend itself to very fast implementations for a wide range of applications where speed is at a premium.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 25, Issue 7, October 2014, Pages 1558–1565
نویسندگان
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