Name
Title | ||
|---|---|---|
A quality-aware Energy-scalable Gaussian Smoothing Filter for image processing applications. |
Abstract | ||
|---|---|---|
Energy-efficient design is the prime requirement for modern portable devices as these devices employ compute intensive image/video processing cores which produces output for human consumption. The limited perception of human sense can be exploited to improve energy-efficacy via approximate designs. In this paper, a novel quality-aware Energy-Scalable Gaussian Smoothing Filter (ES-GSF) is proposed that significantly reduces energy requirement at the cost of slightly reduced quality. The energy scalability within ES-GSF is achieved by exploiting the relative significance of kernel coefficients existing on different boundaries. The ES-GSF computes significant boundaries for the given energy budget. Simulation results show that ES-GSF consumes 30.46% reduced energy with graceful quality degradation over the well-known existing architectures. Further, the ES-GSF can scale energy up to 65.05% when switched from high quality mode to energy-efficient mode. The efficacy of the proposed filter is demonstrated in edge detection where ES-GSF embedded edge detectors consume 29.9% less energy over the well-known existing architectures. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.micpro.2016.02.012 | Microprocessors and Microsystems - Embedded Hardware Design |
Keywords | Field | DocType |
Energy-efficiency,Approximate designs,Gaussian smoothing filter,Edge-detection,Quality-energy tradeoff | Kernel (linear algebra),Video processing,Edge detection,Efficient energy use,Simulation,Computer science,Image processing,Gaussian blur,Real-time computing,Detector,Computer engineering,Scalability | Journal |
Volume | Issue | ISSN |
45 | PA | 0141-9331 |
Citations | PageRank | References |
3 | 0.41 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bharat Garg | 1 | 32 | 9.88 |
| G. K. Sharma | 2 | 29 | 10.22 |