Name
Abstract | ||
|---|---|---|
Lately, stochastic computing (SC) has been found to be significantly advantageous in image processing applications because of its lower hardware complexity and power consumption. However, its viability is deemed to be limited due to excessive run-time requirement. In this paper, a new technique called the variable bit truncation approximate stochastic computing (ASC) approach focusing on image processing applications is proposed to reduce the computation time of a SC with an acceptable trade-off in accuracy. The proposed technique is to variably truncate the low-order bits of the image pixel value depending on the application and the accuracy limits. Experimental results on standard test images for multiple image processing applications suggest that by using this approach acceptable output images can be generated using stochastic computation at a much faster way. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISOCC.2017.8368832 | 2017 International SoC Design Conference (ISOCC) |
Keywords | Field | DocType |
ASC,power consumption,excessive run-time requirement,variable bit truncation approximate stochastic computing approach,low-order bits,image pixel value,standard test images,multiple image processing applications | Noise reduction,Truncation,Approximation algorithm,Computer science,Image processing,Stochastic process,Algorithm,Electronic engineering,Pixel,Stochastic computing,Computation | Conference |
ISSN | ISBN | Citations |
2163-9612 | 978-1-5386-2286-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramu Seva | 1 | 0 | 1.69 |
| Prashanthi Metku | 2 | 0 | 2.70 |
| Kyung Ki Kim | 3 | 99 | 21.62 |
| Yong-Bin Kim | 4 | 22 | 7.14 |
| Minsu Choi | 5 | 156 | 27.63 |