Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6864878 | Neurocomputing | 2018 | 12 Pages |
Abstract
Most haze removal methods fail to restore long-shot images naturally, especially for the sky region. To solve this problem, we proposed a Fusion of Luminance and Dark Channel Prior (F-LDCP) method to effectively restore long-shot images with sky. The transmission values estimated based on a luminance model and dark channel prior model are fused together based on a soft segmentation. The transmission estimated from the luminance model mainly contributes to the sky region, while that from the dark channel prior for the foreground region. The airlight also is adjusted to adapt to real light by sky region detection. A user study and objective assessment comparison with a variety of methods on long-shot haze images demonstrate that our method retains visual truth and removes the haze effectively.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yingying Zhu, Gaoyang Tang, Xiaoyan Zhang, Jianmin Jiang, Qi Tian,