Results 81 to 90 of about 11,243,828 (208)
Image and video dehazing by regularized optimization
, 2017 Images and videos captured in hazy weather often yield low contrast and offer limited visibility due to the presence of haze in the atmosphere. Dr Jiaxi studied the image and video dehazing problem.
Jiaxi He (3115425)
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Nighttime image dehazing based on Retinex and dark channel prior using Taylor series expansion
, 2020 © 2020 Elsevier Inc. Haze removal from nighttime images is more difficult compared with daytime image dehazing due to the uneven illumination, low contrast and severe color distortion.
Liu, H +5 more
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GRA‐Net: Geometry‐ and Response‐Aware Convolutional Network for Nighttime Deflaring
IET Image Processing, Volume 20, Issue 1, January/December 2026.We propose GRA‐Net, a geometry‐ and response‐aware convolutional network for nighttime flare removal in autonomous driving images. The network achieves unified spatio‐photometric flare rectification by leveraging geometric priors and adaptive illumination responses. Experiments on the Flare7K++ dataset show that GRA‐Net outperforms existing lightweight
Wei Lu +5 more
wiley +1 more source
Mean‐Local Binary Pattern‐Guided Multi‐Attention Network for Low‐Light Image Enhancement
IET Image Processing, Volume 20, Issue 1, January/December 2026.Low‐light image enhancement struggles with noise amplification, residual dark areas, artefacts and detail loss. This paper presents the MGA‐LLIEN network, which uses M‐LBP for adaptive brightness adjustment and detail recovery while reducing noise and outperforms leading methods in tests. ABSTRACT Low‐light image enhancement faces key challenges: noise
Binxin Tang +4 more
wiley +1 more source
Single image dehazing with white balance correction and image decomposition
, 2012 Single image dehazing has been a challenging problem due to its ill-posed nature. While most of the existing single image based dehazing algorithms address this issue by introducing certain assumptions and priors into the haze imaging model, the imaging ...
Xiong, H +7 more
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Diffusion Models and Its Applications in Image Dehazing: A Survey
IET Image Processing, Volume 20, Issue 1, January/December 2026.1.This survey represents the first systematic and comprehensive overview of diffusion model‐based image dehazing, aiming to provide a valuable guide for future researchers and stimulate continued progress in this field. 2.We summarize relevant papers along with their corresponding code links and other resources for image dehazing and all‐in‐one image ...
Liangyu Zhu +6 more
wiley +1 more source
Deeplearning method for single image dehazing based on HSI colour space
Journal of Measurement Science and Instrumentation, 2021 The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space for single image dehazing is proposed
CHEN Yong, TAO Meifeng, GUO Hongguang
doaj
IEEE Access, 2020 An end-to-end image dehazing method based on convolution neural network is presented to solve the problem in which Unmanned Aerial Vehicle (UAV) high-resolution remote sensing images have reduced image sharpness due to haze.
Yufeng Li, Jingbo Ren, Yufeng Huang
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IET Image Processing, Volume 20, Issue 1, January/December 2026.This study proposes Swin‐attention‐enhanced atrous spatial pyramid pooling (ASPP)‐attention‐squeeze‐and‐excitation (SE) uncertainty‐aware U‐Net++ (SAASU‐UNet++), a novel hybrid deep learning framework for breast tumour segmentation in ultrasound images.
Rahul Singh +6 more
wiley +1 more source
An improved image dehazing and enhancing method using dark channel prior
, 2015 In fog and haze weather conditions, the outdoor visibility is greatly reduced by the atmospheric scattering. Images taken in this weather suffer from serious degradation.
Luo HB(罗海波) +3 more
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