FPGA-based Scalable Road Image Stochastic Denosing Approach
Cheolhyeong Park, Kyung Ki Kim, Yong-Bin Kim, Minsu Choi · 2021
This work proposes FPGA-based stochastic computing for efficient and scalable road image stochastic denoising. Stochastic number generators were compared for fields requiring data reliability such as automotive vehicles. The denoising performance of PRNG (Pseudo-Random Number Generator) and LDSG (Low Discrepancy Sequence Generator) are showed in noised KETTI dataset with filtering algorithms. The proposed approach is expected to be easily applied to SoCs with embedded FPGA for lightweight embedded implementation of image denoising algorithms.