25,041 research outputs found

    Enhanced low bitrate H.264 video coding using decoder-side super-resolution and frame interpolation

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    Advanced inter-prediction modes are introduced recently in literature to improve video coding performances of both H.264 and High Efficiency Video Coding standards. Decoder-side motion analysis and motion vector derivation are proposed to reduce coding costs of motion information. Here, we introduce enhanced skip and direct modes for H.264 coding using decoder-side super-resolution (SR) and frame interpolation. P-and B-frames are downsampled and H.264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Alternatively for B-frames, bidirectional true motion estimation is performed to synthesize a B-frame from its reference frames. For P-frames, bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm is developed to decide for each MB which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.04 dB peak signal-to-noise ratio (PSNR) improvement or 23.0% bitrate reduction at low bitrates when compared with H.264 standard. The PSNR gains reach as high as 3.00 dB for inter-predicted frames and 3.78 dB when only B-frames are considered. Decoded videos exhibit significantly better visual quality as well.This research was supported by TUBITAK Career Grant 108E201Publisher's Versio

    An efficient fast mode decision algorithm for H.264/AVC intra/inter predictions

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    H.264/AVC is the newest video coding standard, which outperforms the former standards in video coding efficiency in terms of improved video quality and decreased bitrate. Variable block size based mode decision (MD) with rate distortion optimization (RDO) is one of the most impressive new techniques employed in H.264/AVC. However, the improvement on performance is achieved at the expense of significantly increased computational complexity, which is a key challenge for real-time applications. An efficient fast mode decision algorithm is then proposed in this paper. By exploiting the correlation between macroblocks and the statistical characteristics of sub-macroblock in MD, the video encoding time can be reduced 52.19% on average. Furthermore, the motion speed based adjustment scheme was introduced to minimize the degradation of performanc

    Reducing the complexity of a multiview H.264/AVC and HEVC hybrid architecture

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    With the advent of 3D displays, an efficient encoder is required to compress the video information needed by them. Moreover, for gradual market acceptance of this new technology, it is advisable to offer backward compatibility with existing devices. Thus, a multiview H.264/Advance Video Coding (AVC) and High Efficiency Video Coding (HEVC) hybrid architecture was proposed in the standardization process of HEVC. However, it requires long encoding times due to the use of HEVC. With the aim of tackling this problem, this paper presents an algorithm that reduces the complexity of this hybrid architecture by reducing the encoding complexity of the HEVC views. By using Na < ve-Bayes classifiers, the proposed technique exploits the information gathered in the encoding of the H.264/AVC view to make decisions on the splitting of coding units in HEVC side views. Given the novelty of the proposal, the only similar work found in the literature is an unoptimized version of the algorithm presented here. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity

    Mode refinement algorithm for H.264 inter frame requantization

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    3D high definition video coding on a GPU-based heterogeneous system

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    H.264/MVC is a standard for supporting the sensation of 3D, based on coding from 2 (stereo) to N views. H.264/MVC adopts many coding options inherited from single view H.264/AVC, and thus its complexity is even higher, mainly because the number of processing views is higher. In this manuscript, we aim at an efficient parallelization of the most computationally intensive video encoding module for stereo sequences. In particular, inter prediction and its collaborative execution on a heterogeneous platform. The proposal is based on an efficient dynamic load balancing algorithm and on breaking encoding dependencies. Experimental results demonstrate the proposed algorithm's ability to reduce the encoding time for different stereo high definition sequences. Speed-up values of up to 90× were obtained when compared with the reference encoder on the same platform. Moreover, the proposed algorithm also provides a more energy-efficient approach and hence requires less energy than the sequential reference algorith
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