Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation
The abuse of high beam lights dazzles the opposite drivers when the vehicles meet at night, which can easily cause traffic accidents. The existing night vision anti-halation algorithms based on different-source image fusion can eliminate halation and obtain fusion images with rich color and details....
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MDPI AG
2023-05-01
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Series: | Mathematics |
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Online Access: | https://www.mdpi.com/2227-7390/11/10/2237 |
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author | Quanmin Guo Jiahao Liang Hanlei Wang |
author_facet | Quanmin Guo Jiahao Liang Hanlei Wang |
author_sort | Quanmin Guo |
collection | DOAJ |
description | The abuse of high beam lights dazzles the opposite drivers when the vehicles meet at night, which can easily cause traffic accidents. The existing night vision anti-halation algorithms based on different-source image fusion can eliminate halation and obtain fusion images with rich color and details. However, the algorithms mistakenly eliminate some high-brightness important information. In order to address the problem, a night vision anti-halation algorithm based on low-frequency sequence generation is proposed. The low-frequency sequence generation model is constructed to generate image sequences with different degrees of halation elimination. According to the estimated illuminance for image sequences, the proposed sequence synthesis based on visual information maximization assigns a large weight to the areas with good brightness so as to obtain the fusion image without halation and with rich details. In four typical halation scenes covering most cases of night driving, the proposed algorithm effectively eliminates halation while retaining useful high-brightness information and has better universality than the other seven advanced comparison algorithms. The experimental results show that the fusion image obtained by the proposed algorithm is more suitable for human visual perception and helps to improve night driving safety. |
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issn | 2227-7390 |
language | English |
last_indexed | 2024-03-11T03:32:22Z |
publishDate | 2023-05-01 |
publisher | MDPI AG |
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series | Mathematics |
spelling | doaj.art-786497002f11403fa6182609fc1ecdea2023-11-18T02:18:02ZengMDPI AGMathematics2227-73902023-05-011110223710.3390/math11102237Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence GenerationQuanmin Guo0Jiahao Liang1Hanlei Wang2School of Electronic and Information Engineering, Xi’an Technological University, Xi’an 710021, ChinaSchool of Electronic and Information Engineering, Xi’an Technological University, Xi’an 710021, ChinaSchool of Electronic and Information Engineering, Xi’an Technological University, Xi’an 710021, ChinaThe abuse of high beam lights dazzles the opposite drivers when the vehicles meet at night, which can easily cause traffic accidents. The existing night vision anti-halation algorithms based on different-source image fusion can eliminate halation and obtain fusion images with rich color and details. However, the algorithms mistakenly eliminate some high-brightness important information. In order to address the problem, a night vision anti-halation algorithm based on low-frequency sequence generation is proposed. The low-frequency sequence generation model is constructed to generate image sequences with different degrees of halation elimination. According to the estimated illuminance for image sequences, the proposed sequence synthesis based on visual information maximization assigns a large weight to the areas with good brightness so as to obtain the fusion image without halation and with rich details. In four typical halation scenes covering most cases of night driving, the proposed algorithm effectively eliminates halation while retaining useful high-brightness information and has better universality than the other seven advanced comparison algorithms. The experimental results show that the fusion image obtained by the proposed algorithm is more suitable for human visual perception and helps to improve night driving safety.https://www.mdpi.com/2227-7390/11/10/2237night vision anti-halationdifferent source image fusionlow-frequency sequence generationilluminance estimationYUV transformcurvelet transform |
spellingShingle | Quanmin Guo Jiahao Liang Hanlei Wang Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation Mathematics night vision anti-halation different source image fusion low-frequency sequence generation illuminance estimation YUV transform curvelet transform |
title | Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation |
title_full | Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation |
title_fullStr | Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation |
title_full_unstemmed | Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation |
title_short | Night Vision Anti-Halation Algorithm of Different-Source Image Fusion Based on Low-Frequency Sequence Generation |
title_sort | night vision anti halation algorithm of different source image fusion based on low frequency sequence generation |
topic | night vision anti-halation different source image fusion low-frequency sequence generation illuminance estimation YUV transform curvelet transform |
url | https://www.mdpi.com/2227-7390/11/10/2237 |
work_keys_str_mv | AT quanminguo nightvisionantihalationalgorithmofdifferentsourceimagefusionbasedonlowfrequencysequencegeneration AT jiahaoliang nightvisionantihalationalgorithmofdifferentsourceimagefusionbasedonlowfrequencysequencegeneration AT hanleiwang nightvisionantihalationalgorithmofdifferentsourceimagefusionbasedonlowfrequencysequencegeneration |