A GPU-Accelerated Modified Unsharp-Masking Method for High-Frequency Background- Noise Suppression
Journal
IEEE Access
Journal Volume
9
Pages
68746-68757
Date Issued
2021
Author(s)
Abstract
A digitized analog signal often encounters a high-frequency noisy background which degrades the signal-to-noise ratio (SNR) particularly in case of low signal strength. Despite quite a lot of hardware- and software-based approaches have been reported to date to deal with the noise issue, it is still a challenging task to real-time retrieve the noise-contaminated low-frequency information efficiently without degrading the original bandwidth. In this paper, we report a modified unsharp-masking (UM)-based Graphics Processing Unit (GPU)-accelerated algorithm to efficiently suppress a high-frequency noisy background in a digitized two-dimensional image. The proposed idea works effectively even if noise-density is high and signal of interest is comparable or weaker than the maximum noise level. While suppressing the noisy background, the original resolution remains least compromised. We first explore the effectiveness of the algorithm by means of simulated images and subsequently extend our demonstration towards a real-world life-science imaging application. Securing a potential for real-time applicability, we implement the algorithm via Compute Unified Device Architecture (CUDA)-acceleration and preserve a $ < 300~\mu \text{s}$ processing time for a $1000\times 1000$ -sized 8-bit data set. ? 2013 IEEE.
Subjects
Computer graphics; Computer graphics equipment; Computerized tomography; Graphics processing unit; Program processors; Background noise; Compute Unified Device Architecture(CUDA); Hardware and software; High frequency HF; Imaging applications; Maximum noise levels; Signal of interests; Two dimensional images; Signal to noise ratio
Type
journal article