  This paper presents an in-memory computing (IMC) architecture for image
denoising. The proposed SRAM based in-memory processing framework works in
tandem with approximate computing on a binary image generated from neuromorphic
vision sensors. Implemented in TSMC 65nm process, the proposed architecture
enables approximately 2000X energy savings (approximately 222X from IMC)
compared to a digital implementation when tested with the video recordings from
a DAVIS sensor and achieves a peak throughput of 1.25-1.66 frames/us.
