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Dynamic Dark Channel Prior Dehazing with Polarization
Applied Sciences, 2023 For traditional dark channel prior (DCP) imaging through haze environments, intensity information acts as the carrier to acquire the reflective character of the dehazed target image. We introduce polarization as auxiliary information into the traditional
Haotong Suo +6 more
doaj +6 more sources
Single-Image Dehazing Based on Improved Bright Channel Prior and Dark Channel Prior
Electronics (Switzerland), 2023 Single-image dehazing plays a significant preprocessing role in machine vision tasks. As the dark-channel-prior method will fail in the sky region of the image, resulting in inaccurately estimated parameters, and given the failure of many methods to ...
Hao Zhou, Hailing Xiong
exaly +4 more sources
Image Defogging Framework Using Segmentation and the Dark Channel Prior [PDF]
Entropy, 2021 Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision.
Sabiha Anan +5 more
doaj +7 more sources
A Single Image Enhancement Technique Using Dark Channel Prior
Applied Sciences, 2021 In this paper, we propose a novel single image enhancement technique for defogging by using dark channel prior. The traditional dark channel prior methods for defogging have problems of high time complexity, edge effect, and failure of dark channel prior.
Cong Wang +3 more
doaj +4 more sources
Adaptive Tolerance Dehazing Algorithm Based on Dark Channel Prior [PDF]
Algorithms, 2020 The tolerance mechanism based on dark channel prior (DCP) of a single image dehazing algorithm is less effective when there are large areas of the bright region in the hazy image because it cannot obtain the tolerance adaptively according to the ...
Fan Yang, ShouLian Tang
doaj +4 more sources
Generalization of the Dark Channel Prior for Single Image Restoration [PDF]
IEEE Transactions on Image Processing, 2018 Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media.
Yan-Tsung Peng, Keming Cao, P. Cosman
semanticscholar +6 more sources
Self-supervised zero-shot dehazing network based on dark channel prior [PDF]
Frontiers of Optoelectronics, 2023 Most learning-based methods previously used in image dehazing employ a supervised learning strategy, which is time-consuming and requires a large-scale dataset. However, large-scale datasets are difficult to obtain.
Xinjie Xiao +4 more
doaj +2 more sources
Enhanced CycleGAN Network with Adaptive Dark Channel Prior for Unpaired Single-Image Dehazing. [PDF]
Entropy (Basel), 2023 Unpaired single-image dehazing has become a challenging research hotspot due to its wide application in modern transportation, remote sensing, and intelligent surveillance, among other applications. Recently, CycleGAN-based approaches have been popularly
Xu Y, Zhang H, He F, Guo J, Wang Z.
europepmc +2 more sources
Virtual cleaning of sooty mural hyperspectral images using the LIME model and improved dark channel prior. [PDF]
Sci RepMurals, as important carriers of cultural heritage and historical records, showcase artistic, aesthetic, social, and political significance. In ancient times, religious activities such as burning incense and candles in temples led to many murals being ...
Sun P +6 more
europepmc +2 more sources
Dehazing with Dark Channel Prior: Analysis and Implementation
Image Processing On LineIn outdoor scenes, atmospheric absortion and scattering attenuate the radiance received by the camera and may produce haze. In 2009 He et al. proposed a simple but effective dehazing algorithm based on a hypothesis called the ‘dark channel prior’ (DCP ...
J. Lisani, C. Hessel
semanticscholar +2 more sources