Results 31 to 40 of about 36,775 (242)

NTIRE 2020 Challenge on NonHomogeneous Dehazing

, 2020
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze ...
Ancuti, Codruta O., Ancuti, Cosmin, Chang, Jerome, Chang, Yu-Bang, Chao, Ju-Chin, Chen, Peng-Wen, Chen, Siyi, Cherukuri, Venkateswararao, Chuang, Shiue-Yuan, Das, Sourya Dipta, de Dravo, Vincent Whannou, Deng, Qili, Do, Jeonghyeok, Dong, Yu, Dutta, Saikat, Estrada, Dennis, Guo, Tiantong, Hsu, Po-Min, Huang, Ziling, Kim, Munchurl, Kong, Xiangzhen, Lee, David, Li, Xuelu, Liao, Tzu-Yi, Lin, Chang-Hong, Lin, Tsung-Nan, Liu, Jing, Ma, Lizhuang, Mandal, Murari, Mehra, Aryan, Metwaly, Kareem, Monga, Vishal, Narang, Pratik, Ouyang, Bing, Park, Jongmin, Qu, Yanyun, Raghunath, Navaneeth, Su, Tianqi, Sun, Bangyong, Sun, Chung-En, Timofte, Radu, Vasluianu, Florin-Alexandru, Wang, Meiqi, Wang, Zhan-Han, Wu, Haiyan, Wu, Pei-Yuan, Xie, Yuan, Yang, Tsung-Shan, Yu, Mingzhao, Yu, Zhe, Zhao, Xuan, Zhou, Hongyu   +51 more
core   +1 more source

Haze effect removal from image via haze density estimation in optical model

Optics Express, 2013
Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors,
Chia-Hung, Yeh, Li-Wei, Kang, Ming-Sui, Lee, Cheng-Yang, Lin   +3 more
openaire   +2 more sources

Seasonal variation of the transport of black carbon aerosol from the Asian continent to the Arctic during the ARCTAS aircraft campaign [PDF]

, 2011
Extensive measurements of black carbon (BC) aerosol were conducted in and near the North American Arctic during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) aircraft campaign in April and June-July 2008.
Blake, DR, Diskin, G, Fuelberg, HE, Koike, M, Kondo, Y, Matsui, H, Moteki, N, Sahu, LK, Sessions, WR, Takegawa, N, Wisthaler, A, Zhao, Y   +11 more
core   +1 more source

Polarization-Based Haze Removal Using Self-Supervised Network

Frontiers in Physics, 2022
Atmospheric scattering caused by suspended particles in the air severely degrades the scene radiance. This paper proposes a method to remove haze by using a neural network that combines scene polarization information.
Yingjie Shi, Yingjie Shi, Enlai Guo, Enlai Guo, Lianfa Bai, Lianfa Bai, Jing Han, Jing Han   +7 more
doaj   +1 more source

DesnowNet: Context-Aware Deep Network for Snow Removal

, 2017
Existing learning-based atmospheric particle-removal approaches such as those used for rainy and hazy images are designed with strong assumptions regarding spatial frequency, trajectory, and translucency.
Huang, Shih-Chia, Hwang, Jenq-Neng, Jaw, Da-Wei, Liu, Yun-Fu   +3 more
core   +1 more source

Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing

, 2020
Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.
Das, Sourya Dipta, Dutta, Saikat
core   +1 more source

Titan imagery with Keck adaptive optics during and after probe entry [PDF]

, 2006
We present adaptive optics data from the Keck telescope, taken while the Huygens probe descended through Titan's atmosphere and on the days following touchdown. No probe entry signal was detected. Our observations span a solar phase angle range from 0.05°
Bouchez, Antonin H., Brown, Michael E., de Pater, Imke, Gibbard, Seran G., Marchis, Franck, Roe, Henry G., Schaller, Emily L., Young, Eliot, Ádámkovics, Máte   +8 more
core   +1 more source

Insulator fault feature extraction system of substation equipment based on machine vision

IET Networks, EarlyView., 2022
Abstract The artificial intelligence technology and intelligent automation are more and more widely used, the insulators play a supporting and insulating role in the operation of the grid. The use of machine vision inspection technology to detect insulator faults has become an inevitable trend of the times.
Keruo Jiang, Qiaoqun Xia, Lijun Ma, Xin Xu, Zhipeng Shao   +4 more
wiley   +1 more source

Traffic sign detection and recognition using deep learning-based approach with haze removal for autonomous vehicle navigation

e-Prime: Advances in Electrical Engineering, Electronics and Energy
Autonomous vehicle navigation technology is increasing rapidly. However, automatic sign recognition in complex illumination environments like low-light, hazy regions is a significant challenge in in-vehicle navigation. So, haze removal and robust traffic
A. Radha Rani, Y. Anusha, S.K. Cherishama, S. Vijaya Laxmi   +3 more
doaj   +1 more source

Single image haze removal using content‐adaptive dark channel and post enhancement

IET Computer Vision, 2014
As a challenging problem, image haze removal plays an important role in computer vision applications. The dark channel prior has been widely studied for haze removal since it is simple and effective; however, it still suffers from over‐saturation ...
Bo Li, Shuhang Wang, Jin Zheng, Liping Zheng   +3 more
doaj   +1 more source