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

IF 1.8 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC International Journal of Circuit Theory and Applications Pub Date : 2024-09-05 DOI:10.1002/cta.4230
Tongqing Xu, Tan Yao, Ning Li, JunMing Li, Xinlong Min, Hao Xiao
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Abstract

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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用于彩色图像的高吞吐量灵活无损压缩和解压缩架构
无损图像压缩技术在保证图像质量无损的前提下,缩小图像尺寸以提高传输效率,减少占用的存储空间。其中,LOCO-I/JPEG-LS 算法具有无损压缩率高、计算复杂度低等优点,因此被广泛应用于各种实时应用中。然而,由于 LOCO-I 算法存在上下文相关性的问题,该算法的并行性受到很大限制,这大大限制了硬件实现的吞吐量和实时性。现有的设计通过使用大量硬件成本或直接分块但损失压缩比来实现更高的并行性。为了在并行性和压缩比之间进行权衡,本文提出了一种面向分块的 LOCO-I 错误建模方案,既能实现压缩和解压缩的并行性,又能在分块中实现更好的压缩比。在优化算法的基础上,本文提出了一种高吞吐量灵活无损压缩和解压缩架构(HFCD),它能以更低的硬件成本实现更高的每时钟像素(PPC)。此外,HFCD 还引入了参数共享机制,实现了图像块的随机存取,提高了解压缩的灵活性。实验结果表明,与最先进的技术相比,HFCD 压缩的 PPC 提高了 3.02-13.50 倍。在解压缩方面,得益于我们的优化,HFCD 的速度比软件解决方案提高了 22.4 倍。
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来源期刊
International Journal of Circuit Theory and Applications
International Journal of Circuit Theory and Applications 工程技术-工程:电子与电气
CiteScore
3.60
自引率
34.80%
发文量
277
审稿时长
4.5 months
期刊介绍: The scope of the Journal comprises all aspects of the theory and design of analog and digital circuits together with the application of the ideas and techniques of circuit theory in other fields of science and engineering. Examples of the areas covered include: Fundamental Circuit Theory together with its mathematical and computational aspects; Circuit modeling of devices; Synthesis and design of filters and active circuits; Neural networks; Nonlinear and chaotic circuits; Signal processing and VLSI; Distributed, switched and digital circuits; Power electronics; Solid state devices. Contributions to CAD and simulation are welcome.
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