Proceedings ArticleDOI
Efficient image/video dehazing through haze density analysis based on pixel-based dark channel prior
Chia-Hung Yeh,Li-Wei Kang,Cheng-Yang Lin,Chih-Yang Lin +3 more
- pp 238-241
TLDR
A novel single image-based dehazing framework is proposed to remove haze effects from image/video, where two novel image priors are proposed, called the pixel-based dark channel prior and the pixel -based bright channel prior, to accurately estimate the atmospheric light via haze density analysis.Abstract:
Images/videos of outdoor scenes are usually degraded by the turbid medium in the atmosphere. In this paper, a novel single image-based dehazing framework is proposed to remove haze effects from image/video, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze imaging model, we propose to accurately estimate the atmospheric light via haze density analysis. We can then accurately estimate the transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free image can be recovered with lower computational complexity, which can be naturally extended to video dehazing.read more
Citations
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Proceedings ArticleDOI
Hierarchical rank-based veiling light estimation for underwater dehazing
TL;DR: A single image dehazing approach for underwater images with novel veiling light and transmission estimation steps which deal with issues arising from bright objects through subjective evaluation and with commonly used quantitative measures is introduced.
Proceedings ArticleDOI
Fog removal techniques from images: A comparative review and future directions
TL;DR: A review of state-of-art image enhancement and restoration methods for improving the quality and visibility level of an image which provide clear image in bad weather condition and provides the future scope for working directions in this area for the readers.
A Review on Various Haze Removal Techniques for Image Processing
Manpreet Kaur Saggu,Satbir Singh +1 more
TL;DR: The overall objective of this review paper is to explore the short comings of the earlier presented techniques used in the revolutionary era of image processing applications.
Proceedings ArticleDOI
Combining semantic scene priors and haze removal for single image depth estimation
TL;DR: This work proposes a dual channel prior used for identifying pixels that are unlikely to comply with the dark channel assumption, leading to erroneous depth estimates and leverages semantic segmentation information and patch match label propagation to enforce semantically consistent geometric priors.
Proceedings ArticleDOI
Dehazing technique based on dark channel prior model with sky masking and its quantitative analysis
TL;DR: Dark channel prior - a new prior-gives a significant prediction about the quantity of airlight that causes haze, which improves the visibility with significantly reduced time.
References
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Proceedings ArticleDOI
Bilateral filtering for gray and color images
Carlo Tomasi,Roberto Manduchi +1 more
TL;DR: In contrast with filters that operate on the three bands of a color image separately, a bilateral filter can enforce the perceptual metric underlying the CIE-Lab color space, and smooth colors and preserve edges in a way that is tuned to human perception.
Journal ArticleDOI
Single Image Haze Removal Using Dark Channel Prior
Kaiming He,Jian Sun,Xiaoou Tang +2 more
TL;DR: A simple but effective image prior - dark channel prior to remove haze from a single input image is proposed, based on a key observation - most local patches in haze-free outdoor images contain some pixels which have very low intensities in at least one color channel.
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.