A Perception-Aware Decomposition and Fusion Framework for Underwater Image Enhancement

This paper presents a perception-aware decomposition and fusion framework for underwater image enhancement (UIE). Specifically, a general structural patch decomposition and fusion (SPDF) approach is introduced. SPDF is built upon the fusion of two complementary pre-processed inputs in a perception-a...

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Published inIEEE transactions on circuits and systems for video technology Vol. 33; no. 3; p. 1
Main Authors Kang, Yaozu, Jiang, Qiuping, Li, Chongyi, Ren, Wenqi, Liu, Hantao, Wang, Pengjun
Format Journal Article
LanguageEnglish
Published New York IEEE 01.03.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Decomposition
Fuses
Image color analysis
Image contrast
Image enhancement
image fusion
Image quality
Image reconstruction
patch decomposition
Perception
Task analysis
Underwater
Underwater image
Visualization
Online AccessGet full text

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Abstract This paper presents a perception-aware decomposition and fusion framework for underwater image enhancement (UIE). Specifically, a general structural patch decomposition and fusion (SPDF) approach is introduced. SPDF is built upon the fusion of two complementary pre-processed inputs in a perception-aware and conceptually independent image space. First, a raw underwater image is pre-processed to produce two complementary versions including a contrast-corrected image and a detail-sharpened image. Then, each of them is decomposed into three conceptually independent components, i.e., mean intensity, contrast, and structure, via structural patch decomposition (SPD). Afterwards, the corresponding components are fused using tailored strategies. The three components after fusion are finally integrated via inverting the decomposition to reconstruct a final enhanced underwater image. The main advantage of SPDF is that two complementary pre-processed images are fused in a perception-aware and conceptually independent image space and the fusions of different components can be performed separately without any interactions and information loss. Comprehensive comparisons on two benchmark datasets demonstrate that SPDF outperforms several state-of-the-art UIE algorithms qualitatively and quantitatively. Moreover, the effectiveness of SPDF is also verified on another two relevant tasks, i.e., low-light image enhancement and single image dehazing. The code will be made available soon.
AbstractList This paper presents a perception-aware decomposition and fusion framework for underwater image enhancement (UIE). Specifically, a general structural patch decomposition and fusion (SPDF) approach is introduced. SPDF is built upon the fusion of two complementary pre-processed inputs in a perception-aware and conceptually independent image space. First, a raw underwater image is pre-processed to produce two complementary versions including a contrast-corrected image and a detail-sharpened image. Then, each of them is decomposed into three conceptually independent components, i.e., mean intensity, contrast, and structure, via structural patch decomposition (SPD). Afterwards, the corresponding components are fused using tailored strategies. The three components after fusion are finally integrated via inverting the decomposition to reconstruct a final enhanced underwater image. The main advantage of SPDF is that two complementary pre-processed images are fused in a perception-aware and conceptually independent image space and the fusions of different components can be performed separately without any interactions and information loss. Comprehensive comparisons on two benchmark datasets demonstrate that SPDF outperforms several state-of-the-art UIE algorithms qualitatively and quantitatively. Moreover, the effectiveness of SPDF is also verified on another two relevant tasks, i.e., low-light image enhancement and single image dehazing. The code will be made available soon.
Author Kang, Yaozu
Li, Chongyi
Liu, Hantao
Wang, Pengjun
Jiang, Qiuping
Ren, Wenqi
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  organization: College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China
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Snippet This paper presents a perception-aware decomposition and fusion framework for underwater image enhancement (UIE). Specifically, a general structural patch...
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StartPage 1
SubjectTerms Algorithms
Decomposition
Fuses
Image color analysis
Image contrast
Image enhancement
image fusion
Image quality
Image reconstruction
patch decomposition
Perception
Task analysis
Underwater
Underwater image
Visualization
Title A Perception-Aware Decomposition and Fusion Framework for Underwater Image Enhancement
URI https://ieeexplore.ieee.org/document/9895452
https://www.proquest.com/docview/2784636365
Volume 33
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