Lossless Frame Memory Compression Using Pixel-Grain Prediction and Dynamic Order Entropy Coding

Lian, Xiaojuan; Liu, Zhenyu; Zhou, Wei; Duan, Zhemin

doi:10.1109/tcsvt.2015.2469572

Cited by 32 publications

(23 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, the unfixed lossless compression cannot guarantee that the compressed partitions can be linearly addressed. This paper employs the partition group table (PGT) reported in [29] to handle the irregular address mapping issue. The PGT in [29] records the start point and end point of each compressed block buffered in SDRAM, recording the variable length of all compressed units and facilitating the regular accessing therefore.…”

Section: Hardware Architecture Implementationmentioning

confidence: 99%

“…Embedded compression (EC) is an efficient technique [14] to compress the data before storing them into off‐chip SDRAM, and decompress the data fetched back from SDRAM. There are some EC algorithms and architectures reported in the literature [14–30], lossy EC with fixed compression ratio (CR) and lossless EC with variable CR, as well as block‐based and line‐based EC targeting for different applications such as encoding and display. Lossy EC algorithm with fixed CR is straightforward with simple and efficient data organisation; however, has obvious shortcomings.…”

Section: Introductionmentioning

confidence: 99%

“…There are some literature regarding lossy reference image compression [15–17], some works proposed dual‐mode, lossy and lossless, EC algorithms for memory bandwidth saving [18, 19]. In comparison, more papers proposed lossless EC algorithms [20–29]. Lossless EC is preferred for bandwidth saving without image quality degradation.…”

Section: Introductionmentioning

confidence: 99%

“…As for the prediction stage, two types of algorithms are most frequently used. One is spatial domain prediction such as Differential Pulse Code Modulation (DPCM) scanning [25], hierarchical minimum and difference [19], hierarchical average and copy prediction [22], multi‐mode DPCM and averaging (MDA) prediction [28], and self‐contained directional intra‐prediction inherited from HEVC intra‐prediction [29]. Another type achieves pixel prediction with discrete wavelet transform [18], modified Hadamard transform [20], or similar technique.…”

Section: Introductionmentioning

confidence: 99%

“…As for the entropy coding stage, variable length coding (VLC) is widely used, such methods include adaptive Golomb–Rice (GR) coding [20], GR coding [23], Huffman coding, Unary/Exp‐GR coding [29]. For the sake of the difficulties in implementing high‐throughput VLC hardware, the latest EC schemes such as semi‐fixed‐length (SFL) [26, 28] coding and significant bit truncation (SBT) [22] employ two‐step entropy coding: first, separating the residuals into small groups, then performing FL coding according to the local residual feature of each group.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Lossless image compression algorithm and hardware architecture for bandwidth reduction of external memory

Li¹,

Yin

Fang³

et al. 2017

IET Image Processing

View full text Add to dashboard Cite

Section: Hardware Architecture Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Lossless image compression algorithm and hardware architecture for bandwidth reduction of external memory

Li¹,

Yin

Fang³

et al. 2017

IET Image Processing

View full text Add to dashboard Cite

Low-energy motion estimation memory system with dynamic management

Silveira

Amaral

Povala

et al. 2021

J Real-Time Image Proc

View full text Add to dashboard Cite

The digital video coding process imposes severe pressure on memory traffic, leading to considerable power consumption related to frequent DRAM accesses. External off-chip memory demand needs to be minimized by clever architecture/ algorithm co-design, thus saving energy and extending battery lifetime during video encoding. To exploit temporal redundancies among neighboring frames, the motion estimation (ME) algorithm searches for good matching between the current block and blocks within reference frames stored in external memory. To save energy during ME, this work performs memory accesses distribution analysis of the test zone search (TZS) ME algorithm and, based on this analysis, proposes both a multi-sector scratchpad memory design and dynamic management for the TZS memory access. Our dynamic memory management, called neighbor management, reduces both static consumption-by employing sectorlevel power gating-and dynamic consumption-by reducing the number of accesses for ME execution. Additionally, our dynamic management was integrated with two previously proposed solutions: a hardware reference frame compressor and the Level C data reuse scheme (using a scratchpad memory). This system achieves a memory energy consumption savings of 99.8% and, when compared to the baseline solution composed of a reference frame compressor and data reuse scheme, the memory energy consumption was reduced by 44.1% at a cost of just 0.35% loss in coding efficiency, on average. When compared with related works, our system presents better memory bandwidth/energy savings and coding efficiency results.

show abstract

LL‐FMC: Low‐latency frame memory compression scheme with high reconstructed quality

Shin

Lee

Kim

2023

Electronics Letters

View full text Add to dashboard Cite

Frame memory compression (FMC) saves power by reducing the data bandwidth for accessing reference frames of video coding standards in the external memory. However, since the continuously accumulated data loss degrades the performance of video coding standards, the quality of the reconstructed reference frame must be improved. Previous lossy frame memory compression methods focused on processing speed or simplicity, but their performance remains limited in terms of the quality of the reconstructed frame. In this study, a Huffman coding with a fixed codebook designed to considerably reduce the latency caused by arithmetic coding in lossless compression schemes is proposed. A novel lossy frame memory compression technique based on the Hadamard transform that does not require additional memory access using a lookup table is also proposed. The result of experiments on several reconstructed videos preprocessed with HEVC show that the proposed method improves BDPSNR by 10.7 dB and BDBR by 40.4% compared with the DWT+SPIHT‐based compression technique which is widely used for lossy frame memory compression.

show abstract

Lossless Frame Memory Compression Using Pixel-Grain Prediction and Dynamic Order Entropy Coding

Cited by 32 publications

References 34 publications

Lossless image compression algorithm and hardware architecture for bandwidth reduction of external memory

Lossless image compression algorithm and hardware architecture for bandwidth reduction of external memory

Low-energy motion estimation memory system with dynamic management

LL‐FMC: Low‐latency frame memory compression scheme with high reconstructed quality

Contact Info

Product

Resources

About