Name
Abstract | ||
|---|---|---|
In this letter, a fast and efficient haze removal method is presented. We employ an extremum approximate method to extract the atmospheric light and propose a contour preserving estimation to obtain the transmission by using edge-preserving and mean filters alternately. Our method can efficiently avoid the halo artifact generated in the recovered image. To meet the requirement of real-time applications, an 11-stage pipelined hardware architecture for our haze removal method is presented. It can achieve 200 MHz with 12.8 K gate counts by using TSMC 0.13-$\\mu{\\rm m}$ technology. Simulation results indicate that our design can obtain comparable results with the least execution time compared to previous algorithms and is suitable for low-cost high-performance hardware implementation for haze removal. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TCSVT.2013.2243650 | IEEE Trans. Circuits Syst. Video Techn. |
Keywords | Field | DocType |
hardware architecture,halo artifact,pipelined hardware architecture,mean filters,contour preserving estimation,edge preserving filters,atmospheric light extraction,frequency 200 mhz,image recovery,geophysical image processing,filtering theory,real-time,haze removal,size 0.13 mum,pipeline processing | Computer vision,Computer science,Execution time,Artificial intelligence,Halo,Computer hardware,Filtering theory,Hardware architecture,Haze | Journal |
Volume | Issue | ISSN |
23 | 8 | 1051-8215 |
Citations | PageRank | References |
22 | 1.27 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yeu-Horng Shiau | 1 | 105 | 10.77 |
| Hung-Yu Yang | 2 | 36 | 4.37 |
| Pei-Yin Chen | 3 | 314 | 38.47 |
| Ya-Zhu Chuang | 4 | 22 | 1.27 |