دورية أكاديمية

Radiance–Reflectance Combined Optimization and Structure-Guided $\ell _0$-Norm for Single Image Dehazing.

التفاصيل البيبلوغرافية
العنوان: Radiance–Reflectance Combined Optimization and Structure-Guided $\ell _0$-Norm for Single Image Dehazing.
المؤلفون: Shin, Joongchol, Kim, Minseo, Paik, Joonki, Lee, Sangkeun
المصدر: IEEE Transactions on Multimedia; Jan2020, Vol. 22 Issue 1, p30-44, 15p
مستخلص: Outdoor images are subject to degradation regarding contrast and color because atmospheric particles scatter incoming light to a camera. Existing haze models that employ model-based dehazing methods cannot avoid the dehazing artifacts. These artifacts include color distortion and overenhancement around object boundaries because of the incorrect transmission estimation from a depth error in the skyline and the wrong haze information, especially in bright objects. To overcome this problem, we present a novel optimization-based dehazing algorithm that combines radiance and reflectance components with an additional refinement using a structure-guided $\ell _0$ -norm filter. More specifically, we first estimate a weak reflectance map and optimize the transmission map based on the estimated reflectance map. Next, we estimate the structure-guided $\ell _0$ transmission map to remove the dehazing artifacts. The experimental results show that the proposed method outperforms state-of-the-art algorithms in terms of qualitative and quantitative measures compared with simulated image pairs. In addition, the real-world enhancement results demonstrate that the proposed method can provide a high-quality image without undesired artifacts. Furthermore, the guided $\ell _0$ -norm filter can remove textures while preserving edges for general image enhancement algorithms. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:15209210
DOI:10.1109/TMM.2019.2922127