کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
563143 875472 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Classification-based video super-resolution using artificial neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Classification-based video super-resolution using artificial neural networks
چکیده انگلیسی

In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames. The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction. A classifier is designed based on the edge properties of a pixel in the LR frame to identify the spatial information. To exploit the spatio-temporal information, a motion-trace volume is collected using motion estimation, which can eliminate unfathomable object motion in the LR frames. In addition, temporal lateral process is employed for volume adjustment to reduce unnecessary temporal features. Finally, ANN is applied to each class to learn the complicated spatio-temporal relationship between LR and HR frames. Simulation results show that the proposed method successfully improves both peak signal-to-noise ratio and perceptual quality.


► A super-resolution method using classification and artificial neural network (ANN).
► Pixels are classified based on its spatial property.
► Motion-trace volume is collected using temporal property.
► ANN is used to exploit the spatio-temporal correlation in the motion-trace volume.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 93, Issue 9, September 2013, Pages 2612–2625
نویسندگان
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