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Pixel-level attention based data compression for spike camera
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AI
DOI：10.1007/s11554-024-01618-2.png)
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Abstract
En 中文
With the rapid development of autonomous driving applications, there is an increasing demand for high-speed vision sensors like spike cameras. However, the data transmission and storage requirements are becoming increasingly burdensome due to the high temporal resolution, such as 40,000 Hz. To resolve this problem, we propose a pixel-level attention-based data compression method for the spike camera. First the input spike data are partitioned into two block types by pixel-level attention-based method. Then, the two blocks are condensed using different methods and side information marking is transmitted for spike decoding. Finally, the condensed spike and side information marking are compressed into a binary stream for storage. The experimental results show that our method achieves higher compression efficiency than conventional methods. The decompressed spike can also reconstruct the image with better visual quality.
Keywords:
Spike camera
Spike data compression
Video coding
Spike stream condensation
Journal
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3
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353
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