Name
Abstract | ||
|---|---|---|
In this paper, we propose a adaptive-window-based dehazing method for hazy images. The proposed method is composed of four parts: dark channel measurement, bilateral filtering, atmosphere light and transmission map estimation, and scene radiance recovery. Dissimilar to existing methods, we proposed an adaptive-window-based algorithm to obtain the dark channel. Experimental results demonstrate that the proposed adaptive-window-based method can reduce blocking artifacts in dehazing images and maintain the visual quality of dehazed images high. In addition, the proposed method is faster than the existing method [2]. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/APSIPA.2014.7041765 | APSIPA |
Keywords | Field | DocType |
dark channel measurement,blocking artifact reduction,bilateral filtering,adaptive-window-based image dehazing method,scene radiance recovery,natural scenes,image filtering,transmission map estimation,atmosphere light estimation,pattern recognition,atmosphere,estimation,decision support systems,computer vision,filtering | Computer vision,Computer science,Filter (signal processing),Communication channel,Artificial intelligence,Atmospheric measurements,Bilateral filter,Radiance | Conference |
ISSN | Citations | PageRank |
2309-9402 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guo-Shiang Lin | 1 | 137 | 20.65 |
| Minh-Tuan Nguyen | 2 | 0 | 0.68 |
| Chia-Hung Yeh | 3 | 367 | 42.15 |
| Chih-Yang Lin | 4 | 393 | 48.15 |