scholarly journals Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance

2021 ◽  
Vol 68 (3) ◽  
pp. 3465-3481
Author(s):  
Ghulfam Zahra ◽  
Muhammad Imran ◽  
Abdulrahman M. Qahtani ◽  
Abdulmajeed Alsufyani ◽  
Omar Almutiry ◽  
...  
2021 ◽  
pp. 1-21
Author(s):  
Yu Guo ◽  
Yuxu Lu ◽  
Ryan Wen Liu

Abstract Maritime video surveillance has become an essential part of the vessel traffic services system, intended to guarantee vessel traffic safety and security in maritime applications. To make maritime surveillance more feasible and practicable, many intelligent vision-empowered technologies have been developed to automatically detect moving vessels from maritime visual sensing data (i.e., maritime surveillance videos). However, when visual data is collected in a low-visibility environment, the essential optical information is often hidden in the dark, potentially resulting in decreased accuracy of vessel detection. To guarantee reliable vessel detection under low-visibility conditions, the paper proposes a low-visibility enhancement network (termed LVENet) based on Retinex theory to enhance imaging quality in maritime video surveillance. LVENet is a lightweight deep neural network incorporating a depthwise separable convolution. The synthetically-degraded image generation and hybrid loss function are further presented to enhance the robustness and generalisation capacities of LVENet. Both full-reference and no-reference evaluation experiments demonstrate that LVENet could yield comparable or even better visual qualities than other state-of-the-art methods. In addition, it takes LVENet just 0⋅0045 s to restore degraded images with size 1920 × 1080 pixels on an NVIDIA 2080Ti GPU, which can adequately meet real-time requirements. Using LVENet, vessel detection performance can be greatly improved with enhanced visibility under low-light imaging conditions.


2021 ◽  
Author(s):  
Yu Guo ◽  
Yuxu Lu ◽  
Ryan Wen Liu ◽  
Lizheng Wang ◽  
Fenghua Zhu

2007 ◽  
Vol 33 (2) ◽  
pp. 179-184 ◽  
Author(s):  
Panagiotis Dendrinos ◽  
Eleni Tounta ◽  
Alexandros A. Karamanlidis ◽  
Anastasios Legakis ◽  
Spyros Kotomatas

2018 ◽  
Vol 4 (1) ◽  
pp. 165
Author(s):  
Herry Prabowo ◽  
Mochamad Hilmy

The assessment of the service life of concrete structures using the durability design approach is widely accepted nowadays. It is really encouraged that a simulation model can resemble the real performance of concrete during the service life. This paper investigates the concrete carbonation through probabilistic analysis. Data regarding Indonesian construction practice were taken from Indonesian National Standard (SNI). Meanwhile, data related to Indonesian weather condition for instance humidity and temperature are taken from local Meteorological, Climatological, and Geophysical Agency from 2004 until 2016. Hopefully the results can be a starting point for durability of concrete research in Indonesia.


Sign in / Sign up

Export Citation Format

Share Document