Name
Abstract | ||
|---|---|---|
A general method for image contrast enhancement and noise reduction is proposed in this paper. The method is developed especially for enhancing images acquired under very low light conditions where the features of images are nearly invisible and the noise is serious. By applying an improved and effective image de-haze algorithm to the inverted input image, the intensity can be amplified so that the dark areas become bright and the contrast get enhanced. Then, the joint-bilateral filter with the original green component as the edge image is introduced to suppress the noise. Experimental results validate the performance of the proposed approach. |
Year | Venue | Keywords |
|---|---|---|
2012 | ICPR | very low light conditions,noise suppression,very low light level image noise reduction,image contrast enhancement,edge image,very low light level image enhancement,image denoising,image feature,image de-haze algorithm,feature extraction,inverted input image,joint-bilateral filter,green component,image enhancement |
Field | DocType | ISSN |
Noise reduction,Computer vision,Image gradient,Median filter,Pattern recognition,Computer science,Dark-frame subtraction,Salt-and-pepper noise,Image noise,Artificial intelligence,Image restoration,Edge enhancement | Conference | 1051-4651 |
ISBN | Citations | PageRank |
978-1-4673-2216-4 | 18 | 0.88 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangdong Zhang | 1 | 23 | 3.64 |
| Peiyi Shen | 2 | 217 | 19.72 |
| Lingli Luo | 3 | 18 | 0.88 |
| Liang Zhang | 4 | 64 | 10.30 |
| Juan Song | 5 | 80 | 8.45 |