Results 11 to 20 of about 691 (187)
Efficient Haze Removal from a Single Image Using a DCP-Based Lightweight U-Net Neural Network Model [PDF]
SensorsIn this paper, we propose a lightweight U-net architecture neural network model based on Dark Channel Prior (DCP) for efficient haze (fog) removal with a single input. The existing DCP requires high computational complexity in its operation.
Yunho Han +5 more
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Deep Generative Models for Automated Dehazing Remote Sensing Satellite Images [PDF]
E3S Web of Conferences, 2023 Remote Sensing (RS) is the process of observing and measuring the physical features of an area from a distance by monitoring its reflected and emitted radiation, usually from a satellite or aircraft.
Poornima E. +5 more
doaj +1 more source
ED-Dehaze Net: Encoder and Decoder Dehaze Network [PDF]
, 2022 The presence of haze will significantly reduce the quality of images, such as resulting in lower contrast and blurry details. This paper proposes a novel end-to-end dehazing method, called Encoder and Decoder Dehaze Network (ED-Dehaze Net), which ...
Wei, Yixiong +3 more
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New approach to dehaze single nighttime image
Xibei Gongye Daxue Xuebao, 2021 This paper focus on the dehazing of a single image captured at nighttime. The current state-of-the-art nighttime dehazing approaches usually suffer from the color shift problem due to the fact that the assumptions enforced underdaytime cannot get applied
doaj +1 more source
An Improved Generative Adversarial Network for Image Dehazing [PDF]
Jisuanji gongcheng, 2022 Hazy weather degrades the quality of images obtained by computer vision related systems and affects the normal operation of the system.However, most traditional algorithms establish the relationship between the clear image model and image distortion, and
DING Yongjun, HUANG Shan
doaj +1 more source
Enhanced Variational Image Dehazing [PDF]
SIAM Journal on Imaging Sciences, 2015 Images obtained under adverse weather conditions, such as haze or fog, typically/nexhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling/nthe image structure under the haze layer and recovering vivid colors out of a single image/nremains a challenging task, since the degradation is depth-dependent and
Adrian Galdran +3 more
openaire +3 more sources
Cycle-Dehaze: Enhanced CycleGAN for Single Image Dehazing [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018 In this paper, we present an end-to-end network, called Cycle-Dehaze, for single image dehazing problem, which does not require pairs of hazy and corresponding ground truth images for training. That is, we train the network by feeding clean and hazy images in an unpaired manner.
Deniz Engin +2 more
openaire +3 more sources
DeSmoke-LAP: improved unpaired image-to-image translation for desmoking in laparoscopic surgery [PDF]
, 2022 Purpose Robotic-assisted laparoscopic surgery has become the trend in medicine thanks to its convenience and lower risk of infection against traditional open surgery.
Bano, Sophia +5 more
core +1 more source
Region Adaptive Single Image Dehazing [PDF]
Entropy, 2021 Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility. This problem has been extensively studied in the literature, and the most popular technique is dark channel prior (DCP). However, dark channel prior tends to underestimate
openaire +3 more sources
Fusion-based Variational Image Dehazing [PDF]
IEEE Signal Processing Letters, 2016 We propose a novel image-dehazing technique based on the minimization of two energy functionals and a fusion scheme to combine the output of both optimizations. The proposed fusion-based variational image-dehazing (FVID) method is a spatially varying image enhancement process that first minimizes a previously proposed variational formulation that ...
Adrian Galdran +3 more
openaire +3 more sources