Title :
Geometry-Adaptive Block Partitioning for Intra Prediction in Image & Video Coding
Author :
Dai, Congxia ; Escoda, Òscar Divorra ; Yin, Peng ; Li, Xin ; Gomila, Cristina
Author_Institution :
Thomson Corp. Res., Princeton
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
Many modern video coding strategies, such as the H.264/AVC standard, use quadtree-based partition structures for coding intra macroblocks. Such a structure allows the coding algorithm to adapt to the complicated and non-stationary nature of natural images. Despite the adaptation flexibility of quadtree partitions, recent studies have shown that these are not efficient enough (in terms of rate-distortion performance) when images can be locally modeled as 2D piecewise-smooth signals. These observations motivate us to investigate the use of geometry based block partitioning for modeling intra data in video coding. In particular, in this paper, we study in detail the use of geometry-adaptive intra models, where wedgelet like discontinuities are used in order to define separate coding regions where different statistical/waveform modeling tools can be used. In order to implement this idea, we extend the existing H.264/AVC intra coding scheme by introducing two additional geometric modes: INTRA16X16GEO, and INTRA8X8GEO. Experimental results show that significantly improved R-D performance is achieved.
Keywords :
adaptive codes; block codes; distortion; geometric codes; quadtrees; statistical analysis; video coding; wavelet transforms; 2D piecewise-smooth signal processing; H.264/AVC intracoding standard; geometry-adaptive block partitioning; image coding; intramacroblock coding; quadtree-based partition structure; rate distortion; statistical modeling tool; video coding; waveform modeling tool; Aggregates; Automatic voltage control; Decoding; Geometry; Image coding; Large-scale systems; Partitioning algorithms; Predictive models; Solid modeling; Video coding; Geometric Block Partitioning; H.264/AVC; Intra Prediction; Piecewise-Smooth Signals; Video Coding;
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2007.4379527