کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
529565 869675 2011 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Sparse representations for spatial prediction and texture refinement
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Sparse representations for spatial prediction and texture refinement
چکیده انگلیسی

In this work, we propose a novel approach for signal prediction based on the use of sparse signal representations and Matching Pursuit (MP) techniques. The paper first focuses on spatial texture prediction in a conventional block-based hybrid coding scheme and secondly addresses inter-layer prediction in a scalable video coding (SVC) framework. For spatial prediction the signal reconstruction of the block to predict is based on basis functions selected with the MP iterative algorithm, to best match a causal neighborhood. Inter-layer MP based prediction employs base layer upsampled components additionally to the causal neighborhood in order to improve the representation of high frequencies. New solutions are proposed for efficiently deriving and exploiting the atoms dictionary through phase refinement and mono-dimensional basis functions. Experimental results indicate noticeable improvement of rate/distortion performance compared to the standard prediction methods as specified in H.264/AVC and its extension SVC.

Research highlights
► In this work, we study signal prediction based on sparse signal representations.
► The paper first focuses on texture prediction in a conventional hybrid coding scheme.
► And secondly addresses inter-layer prediction in a scalable video coding framework.
► Solutions are proposed for an efficient use of atoms through phase refinement.
► Experimental results indicate noticeable improvement of rate/distortion performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 22, Issue 8, November 2011, Pages 712–720
نویسندگان
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