Design and research on the JPEG-LS image compression algorithm

Niu, Huizhuo; Shang, Yuanyuan; Yang, Xiaoguang; Xu, Dawei; Han, Baoyuan; Chen, Chuan

doi:10.1109/iccsna.2010.5588699

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…Today, there are many file formats that can efficiently transmit video data over the network at high compression rates [18][19][20][21]. The most commonly used of these are the following:…”

Section: Image Storage File Formatsmentioning

confidence: 99%

Real-Time Network Video Data Streaming in Digital Medicine

Vincze,

Molnar,

Kozlovszky

2023

Computers

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Today, the use of digital medicine is becoming more and more common in medicine. With the use of digital medicine, health data can be shared, processed, and visualized using computer algorithms. One of the problems currently facing digital medicine is the rapid transmission of large amounts of data and their appropriate visualization, even in 3D. Advances in technology offer the possibility to use new image processing, networking, and visualization solutions for the evaluation of medical samples. Because of the resolution of the samples, it is not uncommon that it takes a long time for them to be analyzed, processed, and shared. This is no different for 3D visualization. In order to be able to display digitalized medical samples in 3D at high resolution, a computer with computing power that is not necessarily available to doctors and researchers is needed. COVID-19 has shown that everyday work must continue even when there is a physical distance between the participants. Real-time network streaming can provide a solution to this, by creating a 3D environment that can be shared between doctors/researchers in which the sample being examined can be visualized. In order for this 3D environment to be available to everyone, it must also be usable on devices that do not have high computing capacity. Our goal was to design a general-purpose solution that would allow users to visualize large amounts of medical imaging data in 3D, regardless of the computational capacity of the device they are using. With the solution presented in this paper, our goal was to create a 3D environment for physicians and researchers to collaboratively evaluate 3D medical samples in an interdisciplinary way.

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“…Today, there are many file formats that can efficiently transmit video data over the network at high compression rates [18][19][20][21]. The most commonly used of these are the following:…”

Section: Image Storage File Formatsmentioning

confidence: 99%

Real-Time Network Video Data Streaming in Digital Medicine

Vincze,

Molnar,

Kozlovszky

2023

Computers

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“…JPEG-LS algorithm is based on low complexity lossless compression for images (LOCO-I) algorithm developed by Hewlett-Packard Laboratories [5], which provides lossless compression and near-lossless compression functions. The algorithm only needs to implement data subtraction, shift and other similar, simple processing processes [6]. Compared with joint photographic experts group (JPEG), JPEG2000 and other algorithms, JPEG-LS algorithm has the characteristics of low complexity, easy hardware implementation, etc.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Pipeline Hardware Architecture Design and Implementation for Image Lossless Compression/Decompression Based on JPEG-LS

Liu,

Chen,

Liao

et al. 2024

IEEE Access

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Lossless compression of medical images can reduce data size, save storage and transmission costs, and cope with the challenge of increasing resolution demand for medical images. This paper proposes an adaptive pipeline hardware architecture for lossless compression/decompression of medical images based on joint photographic experts group-lossless (JPEG-LS), which can achieve efficient image processing on field programmable gate array (FPGA). This paper designs an adaptive pipeline architecture based on JPEG-LS algorithm. By adding a pipeline pause mechanism, the problem of coding errors caused by parameter updates is solved. On the one hand, the binary search method is used to optimize the calculation process of the Golomb coding parameter k in the pipeline, which reduces the parameter update delay. On the other hand, the construction process of the context causal template is optimized, which effectively improves the throughput. Based on the parallel block compression architecture, a hardware module for alpha red green blue (ARGB) image block compression/decompression with customizable block size is implemented, which improves the image compression/decompression throughput and reduces the compression and decompression delay. This paper implements the hardware architecture on Zynq7000 FPGA and evaluates its performance. Compared with existing schemes, the proposed architecture uses less resources and achieves higher compression ratio and clock frequency.INDEX TERMS Lossless image compression/decompression, JPEG-LS, hardware design, FPGA

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A Low-Complexity Algorithm for JPEG-LS-Based RAW Domain Compression

Zheng,

Li,

et al. 2023

2023 IEEE 15th International Conference on ASIC (ASICON)

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Design and research on the JPEG-LS image compression algorithm

Cited by 4 publications

References 3 publications

Real-Time Network Video Data Streaming in Digital Medicine

Real-Time Network Video Data Streaming in Digital Medicine

Adaptive Pipeline Hardware Architecture Design and Implementation for Image Lossless Compression/Decompression Based on JPEG-LS

A Low-Complexity Algorithm for JPEG-LS-Based RAW Domain Compression

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