Proceedings ArticleDOI
Efficient Image Dehazing with Boundary Constraint and Contextual Regularization
Gaofeng Meng,Ying Wang,Jiangyong Duan,Shiming Xiang,Chunhong Pan +4 more
- pp 617-624
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TLDR
An efficient regularization method to remove hazes from a single input image and can restore a high-quality haze-free image with faithful colors and fine image details is proposed.Abstract:
Images captured in foggy weather conditions often suffer from bad visibility. In this paper, we propose an efficient regularization method to remove hazes from a single input image. Our method benefits much from an exploration on the inherent boundary constraint on the transmission function. This constraint, combined with a weighted L1-norm based contextual regularization, is modeled into an optimization problem to estimate the unknown scene transmission. A quite efficient algorithm based on variable splitting is also presented to solve the problem. The proposed method requires only a few general assumptions and can restore a high-quality haze-free image with faithful colors and fine image details. Experimental results on a variety of haze images demonstrate the effectiveness and efficiency of the proposed method.read more
Citations
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Proceedings ArticleDOI
Q-DNN: A quality-aware deep neural network for blind assessment of enhanced images
TL;DR: Experimental results on two challenging enhanced image databases show that the proposed data-driven blind image quality assessment (BIQA) method is significantly superior to the state-of-the-art BIQA metrics.
Journal ArticleDOI
CSIDNet: Compact single image dehazing network for outdoor scene enhancement
TL;DR: The experimental results obtained using CSIDNet outperform several well known state-of-the-art dehazing methods in terms of PSNR and SSIM on images of SOTS and HSTS from RESIDE dataset and the visual comparison shows that the dehazed images obtained are more appealing with better edge preservation.
Journal ArticleDOI
Optimisation of transmission map for improved image defogging
TL;DR: Dark channel-based single image defogging technique to estimate atmospheric light which represents the amount of luminance in a scene in the absence of fog to reconstruct fog-free image with a transmission map.
Proceedings ArticleDOI
Thin Cloud Removal Using Local Minimization and Logarithm Image Transformation in HSI Color Space
TL;DR: The proposed method can remove clouds that are not extremely opaque and preserve the actual information such as color and texture due to the higher contrast gain in the experiments comparing to the results obtained from other single-image methods.
Journal ArticleDOI
A cascaded approach for image defogging based on physical and enhancement models
TL;DR: The proposed cascade strategy is based on the combination of enhancement and physical models, the contrast limited adaptive histogram equalization (CLAHE) and no-black pixel constraint with planar assumption (NBPC) methods, which provides better defogging results for homogeneous as well as inhomogeneous fog.
References
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Proceedings ArticleDOI
Visibility in bad weather from a single image
TL;DR: A cost function in the framework of Markov random fields is developed, which can be efficiently optimized by various techniques, such as graph-cuts or belief propagation, and is applicable for both color and gray images.
Journal ArticleDOI
Single image dehazing
TL;DR: Results demonstrate the new method abilities to remove the haze layer as well as provide a reliable transmission estimate which can be used for additional applications such as image refocusing and novel view synthesis.
Journal ArticleDOI
Contrast restoration of weather degraded images
TL;DR: A physics-based model is presented that describes the appearances of scenes in uniform bad weather conditions and a fast algorithm to restore scene contrast, which is effective under a wide range of weather conditions including haze, mist, fog, and conditions arising due to other aerosols.
Journal ArticleDOI
Edge-preserving decompositions for multi-scale tone and detail manipulation
TL;DR: This paper advocates the use of an alternative edge-preserving smoothing operator, based on the weighted least squares optimization framework, which is particularly well suited for progressive coarsening of images and for multi-scale detail extraction.
Journal ArticleDOI
Vision and the Atmosphere
TL;DR: This work studies the visual manifestations of different weather conditions, and model the chromatic effects of the atmospheric scattering and verify it for fog and haze, and derives several geometric constraints on scene color changes caused by varying atmospheric conditions.