RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm

Author:

Hwang Shin-Hyuk1,Park Se-Kil2ORCID,Park Sung-Hyun1ORCID,Kwon Ki-Won3,Im Tae-Ho1ORCID

Affiliation:

1. Department of Information and Communication Engineering, Hoseo University, 20, Hoseo-ro79beon-gil, Baebang-eup, Asan-si 31499, Republic of Korea

2. Korea Research Institute of Ships and Ocean Engineering (KRISO), 32, Yuseong-daero 1312beon-gil, Yuseong-gu, Daejeon 34103, Republic of Korea

3. Korea Electronics Technology Institute (KETI), 25, Saenari-ro, Bundang-gu, Seongnam-si 13509, Republic of Korea

Abstract

A number of accidents at sea are primarily caused by low visibility due to sea fog. Therefore, it is important to estimate sea fog intensity and visibility in real-time in the ocean environment. Visibility meters utilize optical sensors rather than visional information, so that the measured visibility data occasionally includes errors. Moreover, visibility meters have significant costs so that it is not viable to install them at various locations. Therefore, this paper proposes an algorithm called RDCP (Reduced Dark Channel Prior), which provides reliable estimation at a low cost by processing images captured from cameras, since they receive identical information as human eyes. For the estimation, the RDCP algorithm firstly acquires dark channels from an ocean image, then applies an optimized threshold value to the dark channels and crops out the sky region in the ocean image. For the estimation performance evaluation, 320 raw images captured from cameras at four different ports in Republic of Korea are used. Considering facilities in oceans, which are usually operated in power-limited environment, the processing time performance of PDCP is also examined. The experiments demonstrate that the RDCP algorithm provides reliable estimation performance in real-time.

Funder

Ministry of Oceans and Fisheries

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Reference25 articles.

1. (2023, October 20). Korea Coast Guard. Available online: https://www.kcg.go.kr/kcg/na/ntt/selectNttInfo.do?nttSn=34010.

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5. (2017). Guide to Meteorological Instruments and Methods of Observation, World Meteorological Organization.

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