Complexity Analysis of Iterative Basis Transformations Applied to Event-Based Signals



: Ieng SH, Lehtonen E, Benosman R

Publisher: FRONTIERS MEDIA SA

: 2018

: Frontiers in Neuroscience

: FRONTIERS IN NEUROSCIENCE

: FRONT NEUROSCI-SWITZ

: ARTN 373

: 12

: 13

: 1662-453X

DOI: https://doi.org/10.3389/fnins.2018.00373

: https://research.utu.fi/converis/portal/detail/Publication/32123815


This paper introduces an event-based methodology to perform arbitrary linear basis transformations that encompass a broad range of practically important signal transforms, such as the discrete Fourier transform (DFT) and the discrete wavelet transform (DWT). We present a complexity analysis of the proposed method, and show that the amount of required multiply-and-accumulate operations is reduced in comparison to frame-based method in natural video sequences, when the required temporal resolution is high enough. Experimental results on natural video sequences acquired by the asynchronous time-based neuromorphic image sensor (ATIS) are provided to support the feasibility of the method, and to illustrate the gain in computation resources.

Last updated on 2024-26-11 at 19:42