A Lossless Color Image Compression Architecture Using a Parallel Golomb-Rice Hardware CODEC

Kim, Hong-Sik; Lee, Joohong; Kim, Hyun‐Jin; Kang, Sungho; Park, Woo Chan

doi:10.1109/tcsvt.2011.2129350

Cited by 26 publications

(2 citation statements)

References 15 publications

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“…Hence, applying these methods to real-time applications is difficult owing to their variable latency. The GR [13] coding algorithm is widely used with DPCM as a representative lossless compression method, and encoded coefficients can be expressed as follows:…”

Section: Prior Workmentioning

confidence: 99%

“…Hence, applying these methods to real‐time applications is difficult owing to their variable latency. The GR [13] coding algorithm is widely used with DPCM as a representative lossless compression method, and encoded coefficients can be expressed as follows:

\begin{equation} Enc_n=(c_{n}-c_{n+1})/2^k+R \end{equation}

where

C_{n}

denotes the n ‐th coefficient of the image block decomposed by HT, and the difference with the next coefficient

C_{n+1}

is divided by 2 k . Subsequently, the quotient is encoded by allocating bits by size, and the remaining R is encoded using a GR code consisting of a prefix code.…”

Section: Prior Workmentioning

confidence: 99%

See 1 more Smart Citation

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

Shin

Lee

Kim

2023

Electronics Letters

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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.

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Section: Prior Workmentioning

confidence: 99%

\begin{equation} Enc_n=(c_{n}-c_{n+1})/2^k+R \end{equation}

where

C_{n}

denotes the n ‐th coefficient of the image block decomposed by HT, and the difference with the next coefficient

C_{n+1}

is divided by 2 k . Subsequently, the quotient is encoded by allocating bits by size, and the remaining R is encoded using a GR code consisting of a prefix code.…”

Section: Prior Workmentioning

confidence: 99%

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

Shin

Lee

Kim

2023

Electronics Letters

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A high‐throughput flexible lossless compression and decompression architecture for color images

Xu,

Yao,

et al. 2024

Circuit Theory & Apps

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Lossless image compression techniques shrink the image size to improve the transmission efficiency and reduce the occupied storage space while ensuring the quality of the image is lossless. Among them, the LOCO‐I/JPEG‐LS algorithm benefits high lossless compression ratio and low computational complexity and thus is widely used for various real‐time applications. However, due to the problems of the context dependency in the LOCO‐I, the parallelism in the algorithm is greatly constrained, which significantly limits the throughput and the real‐time performance of hardware implementations. Existing designs achieve more parallelism by using a lot of hardware costs or straightforward chunking with losing compression ratio. In order to trade off the parallelism and the compression ratio, this paper proposes a chunk‐oriented error modeling scheme for LOCO‐I, which enables parallelism in both compression and decompression and achieves a better compression ratio in chunks. Based on the optimized algorithm, a high‐throughput flexible lossless compression and decompression architecture (HFCD) is proposed, which achieves higher pixel per clock (PPC) with less hardware cost. Additionally, HFCD introduces a parameter sharing mechanism to enable random access of image chunks to improve the flexibility for decompression. Experimental results show that, compared with state‐of‐the‐art works, HFCD achieves 3.02–13.50 times improvement for the PPC of compression. For decompression, benefiting from our optimizations, HFCD achieves 22.4 times speedup compared to the software solution.

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Design of VLSI Architecture of Autocorrelation-Based Lossless Recompression Engine for Memory-Efficient Video Coding Systems

Lee¹,

Chen²,

You³

2013

Circuits Syst Signal Process

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A Lossless Color Image Compression Architecture Using a Parallel Golomb-Rice Hardware CODEC

Cited by 26 publications

References 15 publications

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

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

A high‐throughput flexible lossless compression and decompression architecture for color images

Design of VLSI Architecture of Autocorrelation-Based Lossless Recompression Engine for Memory-Efficient Video Coding Systems

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