Abstract
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.
Recommended Citation
C. Park et al., "FPGA-Based Scalable Road Image Stochastic Denosing Approach," Proceedings - International SoC Design Conference 2021, ISOCC 2021, pp. 351 - 352, Institute of Electrical and Electronics Engineers, Jan 2021.
The definitive version is available at https://doi.org/10.1109/ISOCC53507.2021.9613963
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
FPGA; Image Denoising; Stochastic Number Generator
International Standard Book Number (ISBN)
978-166540174-6
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2021
Comments
Ministry of Trade, Industry and Energy, Grant P0008751