Denoising algorithm based on improved Markov random field for event camera

To solve the problem of the large amount of noise in the event stream output by the event camera, an event stream denoising algorithm based on the probability undirected graph model was introduced. Due to the imaging principle of the camera, the change of the target had certain regularity and correlation in time and space. By mapping the event to the polar coordinate space-time neighborhood, the local correlation of the event was established to build a complete probability graph model. In addition, the improved conditional iterative mode algorithm was used to optimize the iterative solution of model. The experimental results of simulated data generated by the event camera simulator and the real data recorded by DAVIS346 show that the proposed algorithm can effectively remove noise events. Finally, the comparison with the filtering algorithm proves that the algorithm is superior to the filtering algorithm.