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Low Complexity Deblocking Filter Perceptual Optimization for the Hevc Codec

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Low Complexity Deblocking Filter Perceptual Optimization for the Hevc Codec 2011 18th IEEE International Conference on Image Processing LOW COMPLEXITY DEBLOCKING FILTER PERCEPTUAL OPTIMIZATION FOR THE HEVC CODEC Matteo Naccari 1, Catarina Brites 1,2 , João Ascenso 1,3 and Fernando Pereira 1,2 Instituto de Telecomunicações 1 – Instituto Superior Técnico 2, Instituto Superior de Engenharia de Lisboa 3 {matteo.naccari, catarina.brites, joao.ascenso, fernando.pereira}@lx.it.pt ABSTRACT codec. The perceptual optimization is performed by varying the The compression efficiency of the state-of-art H.264/AVC video two aforementioned offsets to minimize a Generalized Block-edge coding standard must be improved to accommodate the compres- Impairment Metric (GBIM) [7], taken as good quality metric to sion needs of high definition videos. To this end, ITU and MPEG quantify the blocking artifacts visibility. The proposed novelty may started a new standardization project called High Efficiency Video be summarized in two main contributions: first, the GBIM is ex- Coding. The video codec under development still relies on trans- tended to consider the new block sizes considered in the TMuC form domain quantization and includes the same in-loop deblock- codec and, second, a low complexity deblocking filter offsets per- ing filter adopted in the H.264/AVC standard to reduce quantiza- ceptual optimization is proposed to improve the GBIM quality tion blocking artifacts. This deblocking filter provides two offsets while significantly reducing the computational resources that to vary the amount of filtering for each image area. This paper would be required by a brute force approach where all possible proposes a perceptual optimization of these offsets based on a offset values would be exhaustively tested. The proposed deblock- quality metric able to quantify the blocking artifacts impact on the ing filter offsets perceptual optimization is parameterized to be- perceived video quality. The proposed optimization involves low come a dynamic, tuneable tool able to provide some additional computational complexity and provides quality improvements with video quality at the cost of some low computational complexity respect to a non-perceptually optimized H.264/AVC deblocking increase at both the encoder and decoder sides since the deblock- filter. Moreover, the proposed optimization allows up to 92% of ing filter is in the coding loop. To the best of the authors’ knowl- complexity reduction regarding a brute force perceptual optimiza- edge, there is no proposal in the literature for a perceptual optimi- tion which exhaustively tests all the possible offsets values. zation of the deblocking filter, notably by varying the deblocking filter offsets of the H.264/AVC standard. Index Terms— Blocking artifacts, H.264/AVC deblocking The remainder of this paper is organized as follows: Section 2 filter, High Efficiency Video Coding, Perceptual optimization. briefly summarizes the relevant coding tools already considered in the HEVC project. In Section 3, the GBIM is briefly presented and 1. INTRODUCTION then its extension to HEVC is proposed. Section 4 proposes the Recent advantages in video capturing and display technologies low complexity deblocking filter offsets perceptual optimization will further increase the presence of high and ultra high definition while Section 5 presents the experimental results. Finally, Section video contents in multimedia mass market applications. To ac- 6 concludes the paper and discusses some future research work. commodate the higher compression efficiency required by these applications, the compression capabilities of the state-of-art 2. RELATED BACKGROUND H.264/AVC video coding standard [1] must be improved. This All the 27 proposals submitted to the JCT-VC CfP were based target is currently gaining evidence with the standardization activi- on a hybrid block-based motion compensated predictive video ties in the High Efficiency Video Coding (HEVC) project. These coding architecture similar to the one used by the H.264/AVC activities are the result of a successful Call for Proposals (CfP) [2], video coding standard and its predecessors. Nevertheless, several issued in January 2010, by ITU and MPEG which joined efforts in novel coding tools were proposed for the following coding mod- the so-called Joint Collaborative Team on Video Coding (JCT- ules: intra prediction, motion compensation, frequency transforma- VC). Given the interesting results provided by many of the CfP tion, entropy coding and in-loop filtering [3], [4]. In the intra cod- proponents [3], the JCT-VC decided to further investigate the most ing process, new spatial prediction directions have been included promising coding tools, integrating them in a video codec called together with the planar prediction mode, allowing to encode an Test Model under Consideration (TMuC) [4]. The Rate-Distortion 8×8 image area by sending only 1 pixel value for the luminance (RD) performance improvement achieved by the TMuC codec is and 2 pixel values for the chrominance components. In the motion mainly due to the novel coding tools which explicitly tackle the compensation process, new block sizes larger than the usual 16×16 higher spatio-temporal redundancy present in high definition vid- macroblock have been defined by means of the more flexible Cod- eos. Moreover, the perceived quality is improved by means of two ing Tree Block (CTB) structure [4]. A CTB is a B×B image area kinds of in-loop filters which reduce the quantization artifacts. which can be recursively quad-tree split. The size B, together with These two kinds of in-loop filters are the adaptive H.264/AVC the maximum splitting level, may vary at sequence level and be deblocking filter [5] and the symmetric Wiener filter [6]. The signalled in the sequence parameter set. These new partitioning H.264/AVC deblocking filter was designed to filter the blocking sizes lead to new integer discrete cosine transform sizes, notably artifacts while preserving image edges. Furthermore, this deblock- 16×16 , 32×32 and 64×64, in addition to the usual H.264/AVC ing filter allows to adaptively modulate the amount of filtering for 4×4 and 8×8 sizes. For the entropy coding process, decoding par- each block edge by means of two offsets [5]. This modulation may allelization and more efficient context modeling for binary arith- be performed by means of an objective quality metric able to ex- metic coding have been proposed. Finally, in the in-loop filtering press the subjective impact of the quantization blocking artifacts. process, the H.264/AVC deblocking filter has been extended to In this context, this paper proposes a novel perceptual optimi- accommodate the new block sizes and a symmetric Wiener filter zation algorithm for the deblocking filter included in the TMuC has been added on top of the deblocking filter to reduce the quanti- 978-1-4577-1302-6/11/$26.00 ©2011 IEEE 749 2011 18th IEEE International Conference on Image Processing zation distortion inside reconstructed blocks [6]. Regarding the in- is not required for the metric computation) and, thus, it can be also loop deblocking filter, the key element in this paper, the current used at the decoder side where the original content is not available. TMuC software includes two alternative filters: the one standard- ized in the H.264/AVC standard and another proposed by the 3.2. The extended generalized block-edge impairment metric Tandberg-Ericsson-Nokia (TEN) consortium which considers 8×8 The baseline GBIM was designed for image partitionings taken as or larger block sizes and has a less complex filter enabling and regular grids of non overlapped B×B blocks where B was equal to disabling logic [8]. As side effect, the TEN filter has lower flexibil- eight [7]. However, the various block sizes adopted in the TMuC ity for varying the filter offsets. Therefore, in this paper, the codec lead to an irregular image partitioning grid. The GBIM ex- H.264/AVC deblocking filter will be considered for the proposed tension towards this irregular image partitioning grids consists in offsets perceptual optimization as it allows more adaptability in the computing Mh,v and Eh,v assuming a regular image partitioning grid offsets variation and, thus, the provision of a more powerful tool to with a block size equal to the smallest size used by the TMuC co- trade-off additional quality with additional complexity. dec and by setting to zero those differences which do not corre- spond to block edges in the irregular partitioning. Therefore, the 3. PROPOSED GENERALIZED BLOCK-EDGE extended GBIM is computed as: IMPAIRMENT METRIC EXTENSION 1. Regular grid partitioning Mh,v and Eh,v computation : For all This section presents the proposed Generalized Block-edge frames, compute Mh,v and Eh,v as specified in [7] over a regular Impairment Metric (GBIM) [7] extension towards the new block image grid with a block size equal to the smallest size used by sizes adopted in the TMuC codec. the TMuC codec for the video sequence being coded (e.g. 4×4 ). 2. Non block edge element suppression in Mh,v and Eh,v : For all 3.1. The baseline generalized block-edge impairment metric frames, set to zero the Mh,v and Eh,v elements which do not corre- The GBIM is an objective metric able to assess the impact of spond to block edges in the irregular TMuC image partitioning. blocking edge artifacts on the quality perceived by a human ob- 3. Frame level GBIM computation : For all frames, compute GBIM f server. The GBIM measures the luminance differences for pixels as in (1). Note that now Mh,v , Eh,v exclude the pixels which do lying at the image block edges and accounts for some Human Vis- not lie at block edges in the irregular partitioning. ual System (HVS) perceptual mechanisms, making its blocking 4. Sequence level GBIM computation : Compute the GBIM seq value artifacts visibility assessment closer to the human observer judge- as the average over all the already computed GBIM f values.
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