# High Throughput Event Filtering: The Interpolation-based DIF Algorithm Hardware Architecture

arXiv: https://arxiv.org/abs/2506.05825 · HTML: https://mlsanity.com/paper/2506.05825/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 30 references that are in the map.
- First posted on arXiv 6 Jun 2025.

## Builds on (most cited first, 10 of 10)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [E-MLB: Multilevel Benchmark for Event-Based Camera Denoising](https://mlsanity.com/paper/2303.11997/) (2023)
- [v2e: From Video Frames to Realistic DVS Events](https://mlsanity.com/paper/2006.07722/) (2020)
- [Neuromorphic Camera Denoising using Graph Neural Network-driven Transformers](https://mlsanity.com/paper/2112.09685/) (2021)
- [Neuromorphic Imaging with Joint Image Deblurring and Event Denoising](https://mlsanity.com/paper/2309.16106/) (2023)
- [Within-Camera Multilayer Perceptron DVS Denoising](https://mlsanity.com/paper/2304.07543/) (2023)
- [Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection](https://mlsanity.com/paper/2004.01689/) (2020)
- [Hardware architecture for high throughput event visual data filtering with matrix of IIR filters algorithm](https://mlsanity.com/paper/2207.00860/) (2022)
- [Fast Window-Based Event Denoising with Spatiotemporal Correlation Enhancement](https://mlsanity.com/paper/2402.09270/) (2024)
- [Foveal-pit inspired filtering of DVS spike response](https://mlsanity.com/paper/2105.14331/) (2021)

## Abstract (arXiv)

In recent years, there has been rapid development in the field of event vision. It manifests itself both on the technical side, as better and better event sensors are available, and on the algorithmic side, as more and more applications of this technology are proposed and scientific papers are published. However, the data stream from these sensors typically contains a significant amount of noise, which varies depending on factors such as the degree of illumination in the observed scene or the temperature of the sensor. We propose a hardware architecture of the Distance-based Interpolation with Frequency Weights (DIF) filter and implement it on an FPGA chip. To evaluate the algorithm and compare it with other solutions, we have prepared a new high-resolution event dataset, which we are also releasing to the community. Our architecture achieved a throughput of 403.39 million events per second (MEPS) for a sensor resolution of 1280 x 720 and 428.45 MEPS for a resolution of 640 x 480. The average values of the Area Under the Receiver Operating Characteristic (AUROC) index ranged from 0.844 to 0.999, depending on the dataset, which is comparable to the state-of-the-art filtering solutions, but with much higher throughput and better operation over a wide range of noise levels.