Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks

The safety of ships during nighttime navigation has always been a major concern. With the widespread application of technologies such as intelligent recognition, intelligent detection, and unmanned ship navigation at night, nighttime maritime light pollution has significantly affected the effectiven...

Full description

Saved in:
Bibliographic Details
Main Authors: Hui Sun, Jingyang Wang, Mingyang Pan, Zongying Liu, Shaoxi Li, Ruolan Zhang, Yang Wei
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/13/1/121
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832588193425260544
author Hui Sun
Jingyang Wang
Mingyang Pan
Zongying Liu
Shaoxi Li
Ruolan Zhang
Yang Wei
author_facet Hui Sun
Jingyang Wang
Mingyang Pan
Zongying Liu
Shaoxi Li
Ruolan Zhang
Yang Wei
author_sort Hui Sun
collection DOAJ
description The safety of ships during nighttime navigation has always been a major concern. With the widespread application of technologies such as intelligent recognition, intelligent detection, and unmanned ship navigation at night, nighttime maritime light pollution has significantly affected the effectiveness of these intelligent technologies and navigation safety. Therefore, effectively eliminating nighttime maritime light pollution has become an urgent challenge that needs to be addressed. This paper presents a model based on spatial frequency blocks (SFBs) to solve the problem of light pollution in nighttime sea images. The model includes ResNet-50, an encoder, a decoder, and a discriminator. To enable the model to better remove the influence of light pollution, this study designs a method of first detecting the light pollution area and then removing it. It extracts image information from the space–frequency domain to help eliminate light pollution and retain more image information. The experimental results show that on the nighttime light pollution dataset, the Peak Signal-to-Noise Ratio (PSNR) of the model is improved to 24.91 compared to the current state-of-the-art image restoration model, while the Frechet inception distance (FID) is reduced to 64.85. At the same time, in the real night environment, the model can better remove light pollution to recover the original nighttime information. It has excellent performance and provides a certain reference value for advancing the safety of nighttime maritime navigation.
format Article
id doaj-art-4686037c1bd948efb41a3e1b1ba4e6cf
institution Kabale University
issn 2077-1312
language English
publishDate 2025-01-01
publisher MDPI AG
record_format Article
series Journal of Marine Science and Engineering
spelling doaj-art-4686037c1bd948efb41a3e1b1ba4e6cf2025-01-24T13:36:55ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113112110.3390/jmse13010121Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency BlocksHui Sun0Jingyang Wang1Mingyang Pan2Zongying Liu3Shaoxi Li4Ruolan Zhang5Yang Wei6Navigation College, Dalian Maritime University, Dalian 116026, ChinaCCCC Water Transportation Consultants Co., Ltd., Beijing 100007, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaShipping Development Center of the Guangxi Zhuang Autonomous Region, Nanning 530025, ChinaThe safety of ships during nighttime navigation has always been a major concern. With the widespread application of technologies such as intelligent recognition, intelligent detection, and unmanned ship navigation at night, nighttime maritime light pollution has significantly affected the effectiveness of these intelligent technologies and navigation safety. Therefore, effectively eliminating nighttime maritime light pollution has become an urgent challenge that needs to be addressed. This paper presents a model based on spatial frequency blocks (SFBs) to solve the problem of light pollution in nighttime sea images. The model includes ResNet-50, an encoder, a decoder, and a discriminator. To enable the model to better remove the influence of light pollution, this study designs a method of first detecting the light pollution area and then removing it. It extracts image information from the space–frequency domain to help eliminate light pollution and retain more image information. The experimental results show that on the nighttime light pollution dataset, the Peak Signal-to-Noise Ratio (PSNR) of the model is improved to 24.91 compared to the current state-of-the-art image restoration model, while the Frechet inception distance (FID) is reduced to 64.85. At the same time, in the real night environment, the model can better remove light pollution to recover the original nighttime information. It has excellent performance and provides a certain reference value for advancing the safety of nighttime maritime navigation.https://www.mdpi.com/2077-1312/13/1/121maritime night light pollutionspatial frequency blocksResNet-50
spellingShingle Hui Sun
Jingyang Wang
Mingyang Pan
Zongying Liu
Shaoxi Li
Ruolan Zhang
Yang Wei
Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
Journal of Marine Science and Engineering
maritime night light pollution
spatial frequency blocks
ResNet-50
title Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
title_full Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
title_fullStr Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
title_full_unstemmed Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
title_short Identification and Removal of Light Pollution in Maritime Night-Time Images Based on Spatial Frequency Blocks
title_sort identification and removal of light pollution in maritime night time images based on spatial frequency blocks
topic maritime night light pollution
spatial frequency blocks
ResNet-50
url https://www.mdpi.com/2077-1312/13/1/121
work_keys_str_mv AT huisun identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT jingyangwang identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT mingyangpan identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT zongyingliu identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT shaoxili identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT ruolanzhang identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks
AT yangwei identificationandremovaloflightpollutioninmaritimenighttimeimagesbasedonspatialfrequencyblocks