High Dynamic Range Imaging with Time-Encoding Spike Camera

As a bio-inspired vision sensor, spike camera records light intensity by accumulating photons and firing a spike once a preset threshold is reached. For high-light regions, the accumulated photons may reach the threshold multiple times within a readout interval, while only one spike can be stored and read out, resulting in incorrect intensity representation and a limited dynamic range. Multi-level (ML) spike camera enhances the dynamic range by introducing a spike-firing counter (SFC) to count spikes within each readout interval for each pixel, and uses different spike symbols to represent the arrival of different amounts of photons. However, when the light intensity becomes even higher, each pixel requires an SFC with a higher bit depth, causing great cost to the manufacturing process. To address these issues, we propose time-encoding (TE) spike camera, which transforms the counting of spikes to recording of the time at which a specific number of spikes (i.e., an overflow) is reached. To encode time information with as few bits as possible, instead of directly utilising a timer, we leverage a periodic timing signal with a higher frequency than the readout signal. Then the recording of overflow moment can be transformed into recording the number of accumulated timing signal cycles until the overflow occurs. Additionally, we propose an image reconstruction scheme for TE spike camera, which leverages the multi-scale gradient features of spike data. This scheme includes a similarity-based pyramid alignment module to align spike streams across the temporal domain and a light intensity-based refinement module, which utilises the guidance of light intensity to fuse spatial features of the spike data. Experimental results demonstrate that TE spike camera effectively improves the dynamic range of spike camera. The source codes and datasets are available at https://github.com/zkzhu123/TESC.