Ultra high definition television (UHDTV) imposes extremely high throughput requirement on video encoders based on High Efficiency Video Coding (H.265/HEVC) and Advanced Video Coding (H.264/AVC) standards. Context-adaptive binary arithmetic coding (CABAC) is the entropy coding component of these standards. In very-large-scale integration implementation, CABAC has known difficulties in being effectively pipelined and parallelized, due to the critical bin-to-bin data dependencies in its algorithm. This paper addresses the throughput requirement of CABAC encoding for UHDTV applications. The proposed optimizations including prenormalization, hybrid path coverage and lookahead rLPS to reduce the critical path delay of binary arithmetic encoding (BAE) by exploiting the incompleteness of data dependencies in rLPS updating. Meanwhile, the number of bins BAE delivers per clock cycle is increased by the proposed bypass bin splitting technique. The context modeling and binarization components are also optimized. As a result, our CABAC encoder delivers an average of 4.37 bins per clock cycle. Its maximum clock frequency reaches 420 MHz when synthesized in 90 nm. The corresponding overall throughput is 1836 Mbin/s that is 62.5% higher than the state-of-the-art architecture.

Ultra-High-Throughput VLSI Architecture of H.265/HEVC CABAC Encoder for UHDTV Applications

We present a novel reconfigurable hardware architecture for interpolation filtering in high efficient video coding that adapts to run-time changes of the number of interpolation filter calls and thereby provides a high potential of energy efficiency. It employs a picture-based prediction scheme to estimate the number of interpolation filter calls at run-time by monitoring the group of pictures history based on video coding structure knowledge. Reconfigurable acceleration engines are developed that can adapt to different filter types. Dynamic composition of different instances of these engines enables different implementation versions with area versus throughput tradeoff. A run-time selection scheme determines the best implementation version for each picture based on the throughput requirements. Compared to state-of-the-art, our architecture reduces resource usage by 57% while supporting various throughputs and video resolutions.

A Reconfigurable Hardware Architecture for Fractional Pixel Interpolation in High Efficiency Video Coding

In video compression, throughputs of entropy encoders based on arithmetic coding are limited. This article presents the architecture of the entropy coder able to process in each clock cycle much more binary symbols than previous works. The architecture takes advantage of the multisymbol implementation of the binary arithmetic coder (BAC) developed earlier. To balance high throughputs of the BAC, fast implementations of binarization, context modeling, and probability model (PM) update are developed. The main improvement in the symbol rate stems from the decomposition of the processing path into many parallel ones. Critical paths associated with state transitions are shortened since each path updates the PM only for one context selected in each clock cycle. The negative impact on the symbol rate is compensated by the context-based symbol reordering. Although paths have variable bin/symbol rates, the applied buffering strategy improves the continuity of two data streams directed to the BAC, separately for context-coded and bypass-mode symbols. The entropy coder synthesized for the 90-nm TSMC technology consumes 273-k gates and operates at 570 MHz. It achieves the average symbol rate of 13.08 bins per clock cycle and the throughput of 7455 Mbins/s for high-quality H.265/HEVC compression.

Multisymbol Architecture of the Entropy Coder for H.265/HEVC Video Encoders

Binary arithmetic coding is a key part of recent video compression standards. Its throughput is limited by the inherent dependencies existing in the algorithm. As a consequence, a higher bin parallelism leads to lower clock frequencies. This paper presents an architecture able to exceed limits existing in previous hardware implementations. The architecture exploits less probable symbols as starting points for long series of bins coded in one clock cycle. The evaluation for four possible cases of the range value allows its update in the pipeline before the delayed selection based on actual value. The adaptive division into series is proposed to make long series more frequent. To shorten critical paths, rMPS variables computed for symbols coded in the same clock cycle are first summed and then added to the low register. Up to 16 bypass-mode symbols can be processed in parallel with context-coded symbols in one clock cycle. The architecture is generative, i.e., its throughput can be scaled with resources without strict limits. For example, the binary arithmetic coder synthesized on 90nm TSMC technology which consumes 101.4k gates and operates at the 570 MHz has the average throughput of 13.4 bins per clock cycle for the high-quality H.265/HEVC compression.

Generative Multi-Symbol Architecture of the Binary Arithmetic Coder for UHDTV Video Encoders

Higher compression efficiency in HEVC encoders comes with increased computational complexity, making real time encoding of high resolution videos a challenging task. This challenge can be addressed by software, yet hardware solutions are more appealing due to their superior performance and low power consumption. This paper presents an FPGA based hardware implementation of an all intra HEVC encoder, which can encode 8 bits per sample, 1920×1080 resolution, 30 frames per second raw video, that is viable in real time even at low operating frequencies. A major obstacle to real time encoding in available architectures is the dependency created by reference generation. Moreover, each coding unit (CU) has to be processed in multiple configurations to determine the most efficient split and prediction mode representation, based on the bit stream generated. We propose a new three stage architecture to reduce these dependencies and increase parallelism. Feedback needed for CU split and prediction direction decision from binarization is avoided by a Hadamard based early decision method. Feedback constrained coefficient and reconstruction derivation module exploits several optimization techniques. All modules can operate at 200 MHz and the encoder can achieve real time encoding with a minimum operating frequency of 140 MHz. The design consumes 83K LUTs, 28K registers, and 34 DSPs when implemented on Xilinx Zynq ZC706.

Real time all intra HEVC HD encoder on FPGA

This paper presents a hardware design of context-based adaptive binary arithmetic coding (CABAC) for the emerging High efficiency video coding (HEVC) standard. While aiming at higher compression efficiency, the CABAC in HEVC also invests a lot of effort in the pursuit of parallelism and reducing hardware cost. Simulation results show that our design processes 1.18 bins per cycle on average. It can work at 357 MHz with 48.940K gates targeting 0.13 μm CMOS process. This processing rate can support real-time encoding for all sequences under common test conditions of HEVC standard conforming to the main profile level 6.1 of main tier or main profile level 5.1 of high tier.

A hardware CABAC encoder for HEVC

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A hardware CABAC encoder for HEVC