کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536435 870523 2013 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fast gradient vector flow computation based on augmented Lagrangian method
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Fast gradient vector flow computation based on augmented Lagrangian method
چکیده انگلیسی

Gradient vector flow (GVF) and generalized GVF (GGVF) have been widely applied in many image processing applications. The high cost of GVF/GGVF computation, however, has restricted their potential applications on images with large size. Motivated by progress in fast image restoration algorithms, we reformulate the GVF/GGVF computation problem using the convex optimization model with equality constraint, and solve it using the inexact augmented Lagrangian method (IALM). With fast Fourier transform (FFT), we provide two novel simple and efficient algorithms for GVF/GGVF computation, respectively. To further improve the computational efficiency, the multiresolution approach is adopted to perform the GVF/GGVF computation in a coarse-to-fine manner. Experimental results show that the proposed methods can improve the computational speed of the original GVF/GGVF by one or two order of magnitude, and are more efficient than the state-of-the-art methods for GVF/GGVF computation.


► We proposed new algorithms for GVF and GGVF computation.
► Our methods are comparable with the MGVF method, and are more simple.
► We applied the proposed methods to GVF snake for image segmentation.
► GVF-based anisotropic diffusion model confirms the validity of our new methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 34, Issue 2, 15 January 2013, Pages 219–225
نویسندگان
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