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Blind Image Deblurring via Weighted Dark Channel Prior
Circuits, Systems, and Signal Processing, 2023Xue Feng +4 more
semanticscholar +2 more sources
Specular Reflection Separation Using Dark Channel Prior
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013We present a novel method to separate specular reflection from a single image. Separating an image into diffuse and specular components is an ill-posed problem due to lack of observations. Existing methods rely on a specular-free image to detect and estimate specularity, which however may confuse diffuse pixels with the same hue but a different ...
Hyeongwoo Kim +3 more
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Single image haze removal using dark channel prior
2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009In this paper, we propose a simple but effective image prior-dark channel prior to remove haze from a single input image. The dark channel prior is a kind of statistics of outdoor haze-free images. It is based on a key observation-most local patches in outdoor haze-free images contain some pixels whose intensity is very low in at least one color ...
Kaiming He, Jian Sun 0001, Xiaoou Tang
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Jet Trajectory Recognition Based on Dark Channel Prior
2016The automatic fire-fighting water cannon is an important device for fire extinguish. By identifying the jet trajectory, the closed-loop control of fire extinguishing process can be realized, which improves the quality and efficiency of the water cannon.
Wenyan Chong +3 more
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A modified dark channel prior for improved dehazing
2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2015Images recorded under tough environment often exhibit problems such as being too light, too dark or not having enough contrast because they are degraded by a number of phenomena like fog, haze, rain and snow. This makes it essential to create accurate, high quality imagery which truly represents the scene.
Deepa Nair, Praveen Sankaran
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Variational Formulation of Dark Channel Prior for Single Image Dehazing
Journal of Mathematical Imaging and Vision, 2022In this paper, we analyze the single image dehazing problem and propose a new variational method to solve it based on the dark channel prior. In the analysis section, we determine the influence that error in estimation of parameters of the haze degradation model has on the reconstructed image and give conclusions that can be used in designing a ...
Vedran Stipetic, Sven Loncaric
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Real‐time single image dehazing using block‐to‐pixel interpolation and adaptive dark channel prior
IET Image Processing, 2015 The authors propose a novel and efficient method for single image dehazing. To accelerate the transmission estimation process, a block-to-pixel interpolation method is used for fine dark channel computation, in which the block-level dark channel is first
Hyunchul Shin
exaly +2 more sources
IEEE Internet of Things Journal
Smoke detection is essential for fire prevention, yet it is significantly hampered by the visual similarities between smoke and fog. To address this challenge, a split top-k attention transformer framework (STKformer) is proposed.
Jiongze Yu +8 more
semanticscholar +1 more source
Smoke detection is essential for fire prevention, yet it is significantly hampered by the visual similarities between smoke and fog. To address this challenge, a split top-k attention transformer framework (STKformer) is proposed.
Jiongze Yu +8 more
semanticscholar +1 more source
Underwater image enhancement by dark channel prior
2015 2nd International Conference on Electronics and Communication Systems (ICECS), 2015Light scattering and color change are two main problems in underwater images. Due to light scattering, incident light gets reflected and deflected multiple times by particles present in the water. This degrades the visibility and contrast of the underwater image.
R. Sathya, M. Bharathi, G. Dhivyasri
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A Study on Dark Channel Prior based Image Enhancement Techniques
2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2020The existence of haze and cloud degrades the quality of the image taken by camera sensors and decreases their clarity. The degradation can majorly be seen using the transmission map, which is one of the crucial parameters of Dehazing using a single image.
Anil Singh Parihar, Gokul Gupta
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