The rising of High Efficiency Video coding (HEVC) standard in the last years to encode Ultra High Definition (UHD) resolution videos bring challenges to both algorithmic and hardware solutions. The entropy encoder, Co...
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ISBN:
(纸本)9781509002474
The rising of High Efficiency Video coding (HEVC) standard in the last years to encode Ultra High Definition (UHD) resolution videos bring challenges to both algorithmic and hardware solutions. The entropy encoder, Context-adaptive binary arithmetic coding (CABAC), presents difficulties to parallelize as well as pipelined with effectiveness. This occurs due to data dependencies in its algorithm. This paper presents an area efficient architecture to deliver the throughput required by CABAC encoding for UHD content. To meet this requirement, we propose optimizations in the renormalization exploiting parallelism, and, we improve the binary arithmetic encoding (BAE) by reducing the critical path delay while increasing the throughput. This technique increases the bins per clock cycle to an average of 2.37. Moreover, simulation results show that our architecture can work at 380MHz with 31.180K gates targeting 0.13μm CMOS process. These results endure support for real-time encoding for all sequences under common test conditions (CTC) of HEVC standard conforming to the main profile.
Complex software appliances can be deployed on hardware with limited available computational resources. This computational boundary puts an additional constraint on software applications. This can be an issue for real...
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ISBN:
(纸本)9781467399623
Complex software appliances can be deployed on hardware with limited available computational resources. This computational boundary puts an additional constraint on software applications. This can be an issue for real-time applications with a fixed time constraint such as low delay video encoding. In the context of High Efficiency Video coding (HEVC), a limited number of publications have focused on controlling the complexity of an HEVC video encoder. In this paper, a technique is proposed to control complexity by deciding between 2N×2N merge mode and full encoding, at different coding Unit (CU) depths. The technique is demonstrated in two encoders. The results demonstrate fast convergence to a given complexity threshold, and a limited loss in rate-distortion performance (on average 2.84% Bjontegaard delta rate for 40% complexity reduction).
To progress the compression performance of standard video coding algorithms, emerging motion compensation techniques will need to be integrated with the current standard techniques such as those used in the H.264. Hig...
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ISBN:
(纸本)9781424456536;9781424456543
To progress the compression performance of standard video coding algorithms, emerging motion compensation techniques will need to be integrated with the current standard techniques such as those used in the H.264. Higher order motion models, geometry-adaptive partitioning and motion-assisted merging are such techniques that can be considered for the next generation of video coders. In this paper, we examine how geometry information can benefit the use of elastic motion models to accomplish better prediction. Relative complexity issues are also discussed which is important in the standardization process. Experimental results suggest that geometry-adaptive block partitioning can add to the performance of elastic motion models to a certain extent, although the increased complexity is of some concern for real-time coding applications.
The latest high efficiency video coding (HEVC) standard achieves about 50% bit-rate reduction at equivalent visual quality compared to H.264/AVC. Sample adaptive offset (SAO) is one of the newly adopted tools right af...
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ISBN:
(纸本)9781467399623
The latest high efficiency video coding (HEVC) standard achieves about 50% bit-rate reduction at equivalent visual quality compared to H.264/AVC. Sample adaptive offset (SAO) is one of the newly adopted tools right after deblocking filter, which can improve both coding efficiency and visual quality. However, for real-time encoding scenarios, the complexity of SAO is usually too high to be enabled. In this paper, a GPU-based optimization algorithm is proposed to reduce the complexity of SAO. Experiments are conducted based on the state-of-the-art open source HEVC encoder, i.e. X265. Results show that the proposed algorithm can reduce about 70% processing time of SAO on average without sacrifice of coding efficiency.
The problem of stabilizing an unstable plant over a noisy communication link is an increasingly important one that arises in problems of distributed control and networked control systems. Although the work of Schulman...
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ISBN:
(纸本)9781612848006
The problem of stabilizing an unstable plant over a noisy communication link is an increasingly important one that arises in problems of distributed control and networked control systems. Although the work of Schulman and Sahai over the past two decades, and their development of the notions of "tree codes" and "anytime capacity", provides the theoretical framework for studying such problems, there has been scant practical progress in this area because explicit constructions of tree codes with efficient encoding and decoding did not exist. To stabilize an unstable plant driven by bounded noise over a noisy channel one needs real-time encoding and real-time decoding and a reliability which increases exponentially with delay, which is what tree codes guarantee. We prove the existence of linear tree codes with high probability and, for erasure channels, give a construction with an expected decoding complexity that is constant per time instant. We give sufficient conditions on the rate and reliability required of the tree codes to stabilize vector plants and argue that they are asymptotically tight. This work takes an important step towards controlling plants over noisy channels, and we demonstrate the efficacy of the method through a simulation.
real-time encoding of video streams is computationally intensive and rarely carried out at high resolutions. In this paper, for the first time, we propose a platform for H.264 encoder which is both flexible (allows so...
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ISBN:
(纸本)9783981537024
real-time encoding of video streams is computationally intensive and rarely carried out at high resolutions. In this paper, for the first time, we propose a platform for H.264 encoder which is both flexible (allows software upgrades) and scalable (supports multiple resolutions), and supports high video quality (by using both intraprediction and inter-prediction) and high throughput (by exploiting slice-level and pixel-level parallelisms). Our platform uses multiple Application Specific Instruction set Processors (ASIPs) with local and shared memories, and hardware accelerators (in the form of custom instructions). Our platform can be configured to use a particular number of ASIPs (slices per video frame) for a specific video resolution at design-time. The MPSoC architecture is automatically generated by our platform and the H.264 software does not need any modification, which enables quick design space exploration. We implemented the proposed platform in a commercial design environment, and illustrated its utility by creating systems with up to 170 ASIPs supporting resolutions up to HD1080. We further show how power gating can be used in our platform to save energy consumption.
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