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基于FPGA的高速相机上原始拜耳图像的并行无损压缩

Parallel Lossless Compression of Raw Bayer Images on FPGA-Based High-Speed Camera.

作者信息

Regoršek Žan, Gorkič Aleš, Trost Andrej

机构信息

Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia.

OptoMotive, Mechatronics Ltd., 1000 Ljubljana, Slovenia.

出版信息

Sensors (Basel). 2024 Oct 15;24(20):6632. doi: 10.3390/s24206632.

Abstract

Digital image compression is applied to reduce camera bandwidth and storage requirements, but real-time lossless compression on a high-speed high-resolution camera is a challenging task. The article presents hardware implementation of a Bayer colour filter array lossless image compression algorithm on an FPGA-based camera. The compression algorithm reduces colour and spatial redundancy and employs Golomb-Rice entropy coding. A rule limiting the maximum code length is introduced for the edge cases. The proposed algorithm is based on integer operators for efficient hardware implementation. The algorithm is first verified as a C++ model and later implemented on AMD-Xilinx Zynq UltraScale+ device using VHDL. An effective tree-like pipeline structure is proposed to concatenate codes of compressed pixel data to generate a bitstream representing data of 16 parallel pixels. The proposed parallel compression achieves up to 56% reduction in image size for high-resolution images. Pipelined implementation without any state machine ensures operating frequencies up to 320 MHz. Parallelised operation on 16 pixels effectively increases data throughput to 40 Gbit/s while keeping the total memory requirements low due to real-time processing.

摘要

数字图像压缩用于减少相机带宽和存储需求,但对高速高分辨率相机进行实时无损压缩是一项具有挑战性的任务。本文介绍了一种基于FPGA的相机上拜耳彩色滤光片阵列无损图像压缩算法的硬件实现。该压缩算法减少了颜色和空间冗余,并采用了哥伦布-莱斯熵编码。针对边缘情况引入了一个限制最大码长的规则。所提出的算法基于整数运算符,以实现高效的硬件实现。该算法首先作为一个C++模型进行验证,随后使用VHDL在AMD-Xilinx Zynq UltraScale+器件上实现。提出了一种有效的树状流水线结构,用于连接压缩像素数据的代码,以生成表示16个并行像素数据的比特流。对于高分辨率图像,所提出的并行压缩可使图像大小减少高达56%。无任何状态机的流水线实现确保了高达320 MHz的工作频率。对16个像素进行并行操作有效地将数据吞吐量提高到40 Gbit/s,同时由于实时处理而使总内存需求保持较低水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79db/11510722/275dcab87103/sensors-24-06632-g001.jpg

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