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Dark and Bright Channel Priors for Haze Removal in Day and Night Images
Intelligent Automation & Soft Computing, 2022Removal of noise from images is very important as a clear, denoised image is essential for any application.In this article, a modified haze removal algorithm is developed by applying combined dark channel prior and multi-scale retinex theory.The combined dark channel prior (DCP) and bright channel prior (BCP) together with the multi-scale retinex (MSR)
U. Hari, A. Ruhan Bevi
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Blind Ultrasound Images Deblurring Based on Quadratic Sparse Bright Channel Prior
2021 The 4th International Conference on Image and Graphics Processing, 2021For an ultrasound blurry image with more dark pixels and the blurry ultrasound image is not sparse enough after the bright channel prior deblurring. In order to make more effective use of the image information and enhance the sparsity of the ultrasound images obtained after deblurring, a method of blind ultrasound image deblurring based on quadratic ...
Qian Ma +4 more
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An Efficient Deep Deblurring Technique Using Dark and Bright Channel Priors
Earth and Environmental Sciences LibraryRanda Atta, Asmaâ Abdallah
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Hybrid single image dehazing with bright channel and dark channel priors
2017 2nd International Conference on Image, Vision and Computing (ICIVC), 2017This paper proposes a novel method combining dark channel prior (DCP) and bright channel prior (BCP) for single image dehazing. The proposed method achieves airlight approximations by implementing numerical proximity of atmospheric light, which use the average value of the DCP and BCP.
Jehoiada Jackson +6 more
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Low-light image enhancement using CNN and bright channel prior
2017 IEEE International Conference on Image Processing (ICIP), 2017In this paper, we propose a joint framework to enhance images under low-light conditions. First, a convolutional neural network (CNN) based architecture is proposed to denoise low-light images. Then, based on atmosphere scattering model, we introduce a low-light model to enhance image contrast.
Li Tao +5 more
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A novel Retinex image enhancement approach via brightness channel prior and change of detail prior
Pattern Recognition and Image Analysis, 2017In this paper, we propose a novel Retinex image enhancement approach by adopting two important prior named brightness channel prior (BCP) and change of detail (CoD) prior. We first derive a rough illumination map estimation method via BCP and Retinex model.
Zhenfei Gu, Mingye Ju, Dengyin Zhang
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$$l_{2}$$ Norm Prior-Based Modified Bright Channel for Low-Illumination Images
2020Low-illumination image enhancement problem is a very challenging problem in many computer vision applications and, when it comes to nighttime low-illumination images, it becomes more challenging because the depth information of the low-illumination image is not known.
Riya, Bhupendra Gupta, Subir Singh Lamba
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Single Image Dehazing using a Weighted Fusion of Dark and Bright Channel Prior with Gamma Correction
2021 2nd International Conference for Emerging Technology (INCET), 2021Nowadays, haze or fog has become a major hurdle for several computer vision applications. The images captured under such scenarios usually have poor visibility. This is because haze primarily affects the air light and hides the scene details. Such images, when directly used for computer vision algorithms, affect the performance of these algorithms and ...
Sudeep D. Thepade +4 more
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Image Dehazing using Dark and Bright Channel Priors and Multi-scale Filters
2020 14th International Conference on Open Source Systems and Technologies (ICOSST), 2020The paper proposes bright and dark channel priors dependent single image based dehazing in two color spaces. The hazy RGB is first converted into YC b C r space. Transmission maps are estimated using dark channel priors (DCPs) and airlight of intensity (in YC b C r ) and RGB components computed using three window sizes.
Nasir Baig +5 more
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Automatic local exposure correction using bright channel prior for under-exposed images
Signal Processing, 2013We address the problem of exposure correction for under-exposed images in this paper. We propose the bright channel prior based on the statistics of well-exposed images. Using the proposed prior, we are able to estimate the relative exposure in local image regions.
Yinting Wang +4 more
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