Image defogging algorithm combining SLIC super-pixel segmentation and transmission optimization.
Saved in:
| Title: | Image defogging algorithm combining SLIC super-pixel segmentation and transmission optimization. |
|---|---|
| Authors: | LI, Jiying1 ljy7609@126.com, LIU, Yu1, LIU, Jie1 |
| Source: | Journal of Measurement Science & Instrumentation. Jun2026, Vol. 17 Issue 2, p267-277. 11p. |
| Subjects: | Image segmentation, Light transmission, Haze, Image processing, Image enhancement (Imaging systems) |
| Abstract: | When images are captured under hazy conditions, light is attenuated and deflected by particle scattering, resulting in reduced brightness and color distortion, which affects the imaging quality of the visual system. This paper proposes a defogging method that combines super-pixel segmentation and transmission optimization. First, the complexity of the haze image was calculated using color entropy to adaptively determine the number of super-pixel blocks. The simple linear iterative clustering (SLIC) super-pixel segmentation method was used to obtain super-pixel blocks with the same features. And the super-pixel block with the highest score was selected as a candidate block to accurately estimate the atmospheric light value. Then, the transmission was estimated using the multiscale dark channel prior and the non-local haze-lines prior, and then the initial transmission after fusion was obtained by wavelet transform. In addition, a guided filter based on unsharp masking was introduced to further improve the transmission estimation accuracy. Finally, an atmospheric scattering model was used to invert the haze-free image. We have conducted a large number of quantitative and qualitative experiments on three datasets, and the results show that the proposed algorithm can achieve a better de-fogging effect, especially in the sky region, where the image restoration effect is more prominent. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Measurement Science & Instrumentation is the property of Journal of Measurement Science & Instrumentation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 195003978 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Image defogging algorithm combining SLIC super-pixel segmentation and transmission optimization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22LI%2C+Jiying%22">LI, Jiying</searchLink><relatesTo>1</relatesTo><i> ljy7609@126.com</i><br /><searchLink fieldCode="AR" term="%22LIU%2C+Yu%22">LIU, Yu</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22LIU%2C+Jie%22">LIU, Jie</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Measurement+Science+%26+Instrumentation%22">Journal of Measurement Science & Instrumentation</searchLink>. Jun2026, Vol. 17 Issue 2, p267-277. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Image+segmentation%22">Image segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Light+transmission%22">Light transmission</searchLink><br /><searchLink fieldCode="DE" term="%22Haze%22">Haze</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Image+enhancement+%28Imaging+systems%29%22">Image enhancement (Imaging systems)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: When images are captured under hazy conditions, light is attenuated and deflected by particle scattering, resulting in reduced brightness and color distortion, which affects the imaging quality of the visual system. This paper proposes a defogging method that combines super-pixel segmentation and transmission optimization. First, the complexity of the haze image was calculated using color entropy to adaptively determine the number of super-pixel blocks. The simple linear iterative clustering (SLIC) super-pixel segmentation method was used to obtain super-pixel blocks with the same features. And the super-pixel block with the highest score was selected as a candidate block to accurately estimate the atmospheric light value. Then, the transmission was estimated using the multiscale dark channel prior and the non-local haze-lines prior, and then the initial transmission after fusion was obtained by wavelet transform. In addition, a guided filter based on unsharp masking was introduced to further improve the transmission estimation accuracy. Finally, an atmospheric scattering model was used to invert the haze-free image. We have conducted a large number of quantitative and qualitative experiments on three datasets, and the results show that the proposed algorithm can achieve a better de-fogging effect, especially in the sky region, where the image restoration effect is more prominent. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Measurement Science & Instrumentation is the property of Journal of Measurement Science & Instrumentation and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=195003978 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.62756/jmsi.1674-8042.2026023 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 267 Subjects: – SubjectFull: Image segmentation Type: general – SubjectFull: Light transmission Type: general – SubjectFull: Haze Type: general – SubjectFull: Image processing Type: general – SubjectFull: Image enhancement (Imaging systems) Type: general Titles: – TitleFull: Image defogging algorithm combining SLIC super-pixel segmentation and transmission optimization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: LI, Jiying – PersonEntity: Name: NameFull: LIU, Yu – PersonEntity: Name: NameFull: LIU, Jie IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 16748042 Numbering: – Type: volume Value: 17 – Type: issue Value: 2 Titles: – TitleFull: Journal of Measurement Science & Instrumentation Type: main |
| ResultId | 1 |
