Accurate Transmission Estimation for Removing Haze and Noise From a Single Image
Accurate Transmission Estimation for Removing Haze and Noise From a Single Image
复制标题
用于消除单幅图像中的雾霾和噪声的准确传输估计
DOI：
10.1109/tip.2019.2949392
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发表时间：
2020
影响因子：
10.6
通讯作者：
Cao Xiaochun
中科院分区：
文献类型：
--
作者：
Wu Qingbo;Zhang Jingang;Ren Wenqi;Zuo Wangmeng;Cao Xiaochun
Image noise usually causes depth-dependent visual artifacts in single image dehazing. Most existing dehazing methods exploit a two-step strategy in the restoration, which inevitably leads to inaccurate transmission maps and low-quality scene radiance for noisy and hazy inputs. To address these problems, we present a novel variational model for joint recovery of the transmission map and the scene radiance from a single image. In the model, we propose a transmission-aware non-local regularization to avoid noise amplification by adaptively suppressing noise and preserving fine details in the recovered image. Meanwhile, to improve the accuracy of transmission estimation, we introduce a semantic-guided regularization to smooth out the transmission map while keeping depth inconsistency at the boundaries of different objects. Furthermore, we design an alternating scheme to jointly optimize the transmission map and the scene radiance as well as the segmentation map. Extensive experiments on synthetic and real-world data demonstrate that the proposed algorithm performs favorably against state-of-the-art dehazing methods on noisy and hazy images.
