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
Reads0
Chats0
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
More filters
Journal ArticleDOI
Single-Image Dehazing via Compositional Adversarial Network
Hongyuan Zhu,Yi Cheng,Xi Peng,Joey Tianyi Zhou,Zhao Kang,Shijian Lu,Zhiwen Fang,Liyuan Li,Joo-Hwee Lim +8 more
TL;DR: This is the first end-to-end generative adversarial model for image dehazing, which simultaneously outputs clean images, transmission maps, and air-lights and remarkably outperforms the state-of-the-art methods.
Book ChapterDOI
Deep Video Dehazing
Wenqi Ren,Xiaochun Cao +1 more
TL;DR: This work develops a deep learning solution for video dehazing, where a CNN is trained end-to-end to learn how to accumulate information across frames for transmission estimation and is subsequently used to recover a haze-free frame via atmospheric scattering model.
Journal ArticleDOI
A Survey on Analysis and Implementation of State-of-the-art Haze Removal Techniques
G. Harish Babu,N. Venkatram +1 more
TL;DR: The current state-of-the-art methods for haze free images, mainly from the last decade, are thoroughly examined in this survey, which systematically summarizes the hardware implementations of various haze removal methods in real time.
Journal ArticleDOI
Perception oriented transmission estimation for high quality image dehazing
TL;DR: Experimental results demonstrate that the proposed algorithm can effectively remove haze and suppress undesirable degradation on dehazed images, both quantitatively and qualitatively, when compared with the state-of-the-art algorithms under dense scattering conditions.
Proceedings ArticleDOI
High-Resolution Image Dehazing with Respect to Training Losses and Receptive Field Sizes
TL;DR: This paper proposes a simple but effective network for high-resolution image dehazing using a conditional generative adversarial network (CGAN), which is called DeHazing GAN (DHGAN), where the hazy patches of scale-reduced training input images are applied to the generator network of DHGAN.
References
More filters
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.