End-to-End Optimized Lossy Compression for Neural-Morphic Spiking Camera Captured Data

doi:10.1109/TCSVT.2025.3530947

	End-to-End Optimized Lossy Compression for Neural-Morphic Spiking Camera Captured Data
	Feng, Kexiang 1,2,3; Jia, Chuanmin 4; Pan, Jingshan 5; Ma, Siwei 6,7; Gao, Wen 6,7,8
	2025-06-01
发表期刊	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN	1051-8215
卷号	35 期号:6 页码:6074-6086
摘要	Recently, the bio-inspired spike camera with continuous motion recording capability has attracted tremendous attention due to its ultra high temporal resolution imaging characteristic. Such imaging feature results in huge data storage and transmission burden compared to that of traditional camera, raising severe challenge and imminent necessity in compression for spike camera captured content. Existing lossy data compression methods could not be applied for compressing spike streams efficiently due to integrate-and-fire characteristic and binarized data structure. Considering the imaging principle and information fidelity of spike cameras, we propose a novel Reconstruction-based Contextual Spike Compression (RCSC) framework, which contains scene reconstruction, contextual image compression and spike generation. To our knowledge, it is the first learning-based model for efficient and robust spike stream compression with informative fidelity. Extensive experimental results show that our model outperforms the state-of-the-art conventional codec VVC intra by 6.14% and surpasses the state-of-the-art learned codec by 2.53% in BD-rate reduction, establishing a strong baseline for spike compression.
关键词	Image coding Cameras Image reconstruction Streams Correlation Redundancy Visualization Firing Spatial resolution Retina Spike compression spatio-temporal contextual compression attention mechanism end-to-end spike coding
DOI	10.1109/TCSVT.2025.3530947
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62025101] ; Beijing Natural Science Foundation[4252003] ; New Cornerstone Science Foundation through the XPLORER PRIZE ; Peking University High-Performance Computing Platform
WOS研究方向	Engineering
WOS类目	Engineering, Electrical & Electronic
WOS记录号	WOS:001506717400039
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/42364
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Jia, Chuanmin; Ma, Siwei
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Comp Sci & Technol, Beijing 100049, Peoples R China 3.Peking Univ, Natl Engn Res Ctr Visual Technol, Beijing 100871, Peoples R China 4.Peking Univ, Wangxuan Inst Comp Technol, Beijing 100080, Peoples R China 5.Shandong Comp Sci Ctr Nat Supercomp Jinan, Jinan 250014, Peoples R China 6.Peking Univ, Natl Engn Res Ctr Visual Technol, Sch Comp Sci, Beijing 100871, Peoples R China 7.Peng Cheng Lab, Shenzhen 518055, Peoples R China 8.Chinese Acad Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Feng, Kexiang,Jia, Chuanmin,Pan, Jingshan,et al. End-to-End Optimized Lossy Compression for Neural-Morphic Spiking Camera Captured Data[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2025,35(6):6074-6086.
APA	Feng, Kexiang,Jia, Chuanmin,Pan, Jingshan,Ma, Siwei,&Gao, Wen.(2025).End-to-End Optimized Lossy Compression for Neural-Morphic Spiking Camera Captured Data.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,35(6),6074-6086.
MLA	Feng, Kexiang,et al."End-to-End Optimized Lossy Compression for Neural-Morphic Spiking Camera Captured Data".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 35.6(2025):6074-6086.