Survey on Algorithm and VLSI Architecture for MPEG-Like Video Coder

Yin, Haibing; Jia, Huizhu; Zhou, Jun; Gao, Zhiyong

doi:10.1007/s11265-016-1160-3

Cited by 8 publications

(7 citation statements)

References 124 publications

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“…These MBs are further divided into smaller sub-blocks of size 4 × 4. Deblocking filter is applied to the reconstructed video frames to improve the visual quality of the video where the vertical edges of every 4×4 block in a MB is filtered followed by the horizontal edges of these sub-blocks [3]. The luma MB is first filtered both vertically and horizontally, followed by Chroma Cb and Chroma Cr [4].…”

Section: Deblocking Filter Algorithm For H264/avcmentioning

confidence: 99%

High-Throughput Deblocking Filter Architecture Using Quad Parallel Edge Filter for H.264 Video Coding Systems

Rajabai

Sivanantham

2019

IEEE Access

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With the increasing demand in electronic gadgets expecting better video quality for multimedia applications, various coding standards evolved for the past two decades and optimization on the architectures of the various modules used in the video codec is most popular. In this paper, an efficient architecture for deblocking filter used to smoothen the pixels of the decompressed video data is proposed, which utilizes both pipelining and parallelism. The filtering process follows a sequential order as filtering vertical edges of luma block and chroma block followed by the horizontal edges of the luma block and chroma block. Three pipeline stages are used and four edges, either vertical or horizontal are filtered in parallel. Internal buffers which hold the sub-blocks read from the external frame buffers are accessed in a ping pong fashion to filter the adjacent sub-edges and thus reducing the external memory access cycles. Due to parallelism with novel edge filtering order, self-transposing mechanism, and ping pong buffer access, the throughput is increased. The proposed quad parallel edge deblocking filter architecture is implemented using Synopsys 90 nm library. It achieves a target area of 19.8 K and can process a Macro Block in 58 clock cycles.

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Section: Deblocking Filter Algorithm For H264/avcmentioning

confidence: 99%

High-Throughput Deblocking Filter Architecture Using Quad Parallel Edge Filter for H.264 Video Coding Systems

Rajabai

Sivanantham

2019

IEEE Access

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“…Even if we improve the communication performance of the network, the lossy compression part will become the bottleneck to transfer the video stream to the abnormal detection part due to the heavy calculation of the compression processes. To overcome the difficulty of improving the lossy compression performance, we can accelerate the compressor and the decompressor by applying GPUs [ 15 ] and dedicated hardware [ 16 ]. However, the lossy compression reduces information of pixels in frames and guarantees the bandwidth of the video stream.…”

Section: Introductionmentioning

confidence: 99%

Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding

Yamagiwa

Ichinomiya

2021

Sensors

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Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for security. Recently, the majority of video encoding mechanisms to reduce the data rate are mainly lossy compression methods such as the MPEG format. However, when we consider special needs for high-speed communication such as display applications and object detection ones with high accuracy from the video stream, we need to address the encoding mechanism without any loss of pixel information, called visually lossless compression. This paper focuses on the Adaptive Differential Pulse Code Modulation (ADPCM) that encodes a data stream into a constant bit length per data element. However, the conventional ADPCM does not have any mechanism to control dynamically the encoding bit length. We propose a novel ADPCM that provides a mechanism with a variable bit-length control, called ADPCM-VBL, for the encoding/decoding mechanism. Furthermore, since we expect that the encoded data from ADPCM maintains low entropy, we expect to reduce the amount of data by applying a lossless data compression. Applying ADPCM-VBL and a lossless data compression, this paper proposes a video transfer system that controls throughput autonomously in the communication data path. Through evaluations focusing on the aspects of the encoding performance and the image quality, we confirm that the proposed mechanisms effectively work on the applications that needs visually lossless compression by encoding video stream in low latency.

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“…It is well known that hardwired throughput is a crucial consideration factor in terms of hardware architecture design, especially for real-time video coder with RD optimization [14], [32]. Parallel processing and pipelining are crucial techniques for efficient implementation with specific throughput constraint on hardware platforms [14], [32]. Efficient pipelining for SDQ is challenged by the inherent data dependencies in trellis search and context state transition in CABAC [14].…”

Section: Introductionmentioning

confidence: 99%

Efficient Hard-Decision Quantization Using an Adaptive Deadzone Offset Model for Video Coding

et al. 2019

Self Cite

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In video coding, rate distortion optimized quantization (RDOQ), a popular version of softdecision quantization (SDQ), achieves superior coding performance, however is ill-suited for hardware implementation due to its inherent sequential processing. On the other hand, deadzone hard-decision quantization (HDQ) is friendly to hardware implementation, however suffers from non-negligible coding performance degradation. This paper proposes a content-adaptive deadzone offset model to improve the coefficient-wise deadzone HDQ by imitating the behavior patterns of RDOQ. The contributions of this paper are characterized by twofold. On one hand, this work formulates seeking optimal deadzone offset model as a problem of binary classification, and analyzes the distribution characteristics of the optimal deadzone offsets obtained from samples by fully imitating RDOQ, and then derives adaptive deadzone offset model by maximizing the right classification probability of offset-induced rounding in HDQ. On the other hand, the distribution parameters of DCT coefficients are measured in a position-wise way, and the adaptive deadzone model is built by applying Maximum a posterior estimation method according to three characteristic parameters, i.e. quantization step size, parameter of DCT coefficients, and quantization remainder, in the sense of rate distortion optimization. Simulation results verify that the proposed adaptive HDQ algorithm, in comparison with fixed-offset HDQ, achieves 0.54% and 0.52% bit rate saving on average with almost negligible complexity increment. Simultaneously, the proposed algorithm only sacrifices smaller than 0.55% and 0.54% increment in terms of BD-BR in comparison with RDOQ. The proposed HDQ is well-suited for hardwired video coding implementation.

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Survey on Algorithm and VLSI Architecture for MPEG-Like Video Coder

Cited by 8 publications

References 124 publications

High-Throughput Deblocking Filter Architecture Using Quad Parallel Edge Filter for H.264 Video Coding Systems

High-Throughput Deblocking Filter Architecture Using Quad Parallel Edge Filter for H.264 Video Coding Systems

Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding

Efficient Hard-Decision Quantization Using an Adaptive Deadzone Offset Model for Video Coding

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