Results 251 to 260 of about 120,890 (299)

Blind Image Deblurring Using Dark Channel Prior

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
We present a simple and effective blind image deblurring method based on the dark channel prior. Our work is inspired by the interesting observation that the dark channel of blurred images is less sparse. While most image patches in the clean image contain some dark pixels, these pixels are not dark when averaged with neighboring highintensity pixels ...
Jinshan Pan, Deqing Sun, Hanspeter Pfister, Ming-Hsuan Yang   +3 more
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Underwater image enhancement by dark channel prior

2015 2nd International Conference on Electronics and Communication Systems (ICECS), 2015
Light 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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Underwater Single Image Restoration Using Dark Channel Prior

2014 Symposium on Automation and Computation for Naval, Offshore and Subsea (NAVCOMP), 2014
The underwater vision is highly spoiled by the underwater degradation effects. As light propagates in the water or other participative mediums, it suffers from a substantial scattering effect that produces poor image quality. Based on a physical model that describes this phenomenon it is possible to recover an haze-free image.
Felipe M. Codevilla, Silvia Silva Da Costa Botelho, Paulo Drews, Nelson Duarte Filho, Joel Felipe De Oliveira Gaya   +4 more
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Single image dehazing using improved dark channel prior

2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN), 2015
Huge quantities of suspended particles in our atmosphere, cause scenes to appear hazy or foggy, this reduces visibility of objects and their contrast, and makes detection of objects within the scene more difficult. Most existing algorithms are based on a strong, statistically based prior, the dark channel prior.
Yogesh Kumar, Jimmy Gautam, Ashutosh Gupta, Bhavin V. Kakani, Himansu Chaudhary   +4 more
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Improved single image dehazing using dark channel prior

2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, 2010
Atmospheric conditions induced by suspended particles, such as fog and haze, severely degrade image quality. Haze removal from a single image of a weather-degraded scene remains a challenging task, because the haze is dependent on the unknown depth information.
null Yan Wang, null Bo Wu
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MODIFIED DARK CHANNEL PRIOR Modified DCP for Dehazing

SSRN Electronic Journal, 2021
The image captured by camera is degraded by various atmospheric parameters for example rain, storm, wind, haze, snow. The removing haze is called dehazing, is naturally done in the physical degradation model, which requires a solution of an ill-posed inverse problem.
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Underwater Enhancement Model via Reverse Dark Channel Prior

2020
The interference of suspended particles causes the problems of color distortion, haze effect and visibility reduction in complex underwater environment. However, existing methods for enhancement often result in overexposure of the low contrast area or distortion of the seriously turbid area. The main factor is the diversity of the underwater images. In
Yue Shen, Haoran Zhao, Xin Sun, Yu Zhang, Junyu Dong   +4 more
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Night video enhancement using improved dark channel prior

2013 IEEE International Conference on Image Processing, 2013
Videos taken under low lighting condition usually have serious loss of visibility and contrast and are inconvenient for observation and analysis. To solve this problem, this paper presents a real-time night video enhancement approach. As observed that a pixel-wise inversion of a night video has quite similar appearance with the video acquired at foggy ...
Xuesong Jiang, Hongxun Yao, Shengping Zhang, Xiusheng Lu, Wei Zeng   +4 more
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Image Haze Removal Based Dark Channel Prior

Applied Mechanics and Materials, 2014
This paper describes the image based on dark channel prior to fog. Dark colors from the statistical laws of outdoor priori no fog image database, it was such a key observation was based on the fact that - the vast majority of each local area outdoor image without fog are present strength of certain of at least one color channel low value pixels.
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A modified dark channel prior for improved dehazing

2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2015
Images 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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