基于去散射与边缘增强算法的水下图像复原

潘攀望; 袁飞; 程恩

doi:10.1631/FITEE.1700744

Your Location：

Home >

Browse articles >

基于去散射与边缘增强算法的水下图像复原

常规文章 | Updated：2022-05-19

- 基于去散射与边缘增强算法的水下图像复原
- De-scattering and edge-enhancement algorithms for underwater image restoration
- 信息与电子工程前沿（英文） 2019年20卷第6期页码：862-871
- Affiliations：
  
  MOE Key Laboratory of Underwater Acoustic Communication and Marine Information Technology, Xiamen University, Xiamen 361005, China
  Department of Communication Engineering, Xiamen University, Xiamen 361005, China
- Author bio：
  
  Fei YUAN, E-mail: yuanfei@xmu.edu.cn
- Funds：
  
  Project supported by the National Natural Science Foundation of China (Nos. 61571377, 61471308, and 61771412) and the Fundamental Research Funds for the Central Universities, China (No. 20720180068)
- DOI：10.1631/FITEE.1700744
  中图分类号： TP391.41
- 收稿：2017-11-10，
  
  修回：2019-;6-11，
  
  纸质出版：2019-06
- Accepted：
Scan QR Code
潘攀望, 袁飞, 程恩. 基于去散射与边缘增强算法的水下图像复原[J]. 信息与电子工程前沿（英文）, 2019,20(6):862-871.

Pan-wang PAN, Fei YUAN, En CHENG. De-scattering and edge-enhancement algorithms for underwater image restoration[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 862-871.
潘攀望, 袁飞, 程恩. 基于去散射与边缘增强算法的水下图像复原[J]. 信息与电子工程前沿（英文）, 2019,20(6):862-871. DOI： 10.1631/FITEE.1700744.

Pan-wang PAN, Fei YUAN, En CHENG. De-scattering and edge-enhancement algorithms for underwater image restoration[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 862-871. DOI： 10.1631/FITEE.1700744.

摘要

对色差严重和边缘模糊的水下图像需进行复原。一般分两步：去散射和边缘增强。首先，提出一种用于水下图像去散射的多尺度迭代框架。利用卷积神经网络估计传输图，再用自适应双边滤波器改进传输图估计结果。由于无可用数据集训练网络，收集包含2000个水下图像的数据集以获得合成数据。其次，采用白平衡算法消除水下图像的色偏。最后将图像转换到特殊变换域，使用非下采样轮廓波变换对边缘去噪和增强。结果表明：该方法主、客观质量均明显优于现有方法。

Abstract

Image restoration is a critical procedure for underwater images

which suffer from serious color deviation and edge blurring. Restoration can be divided into two stages: de-scattering and edge enhancement. First

we introduce a multi-scale iterative framework for underwater image de-scattering

where a convolutional neural network is used to estimate the transmission map and is followed by an adaptive bilateral filter to refine the estimated results. Since there is no available dataset to train the network

a dataset which includes 2000 underwater images is collected to obtain the synthetic data. Second

a strategy based on white balance is proposed to remove color casts of underwater images. Finally

images are converted to a special transform domain for denoising and enhancing the edge using the non-subsampled contourlet transform. Experimental results show that the proposed method significantly outperforms state-of-the-art methods both qualitatively and quantitatively.

关键词

Keywords

references

C Ancuti , , , CO Ancuti , , , T Haber , , , 等 . . Enhancing underwater images and videos by fusion . . IEEE Conf on Computer Vision and Pattern Recognition , , 2012 . . p.81 - - 88 . . DOI: 10.1109/CVPR.2012.6247661 http://doi.org/10.1109/CVPR.2012.6247661 . .

BL Cai , , , XM Xu , , , K Jia , , , 等 . . DehazeNet: an end-to-end system for single image haze removal . . IEEE Trans Image Process , , 2016 . . 25 ( ( 11 ): ): 5187 - - 5198 . . DOI: 10.1109/TIP.2016.2598681 http://doi.org/10.1109/TIP.2016.2598681 . .

N Carlevaris-Bianco , , , A Mohan , , , RM Eustice . . Initial results in underwater single image dehazing . . OCEANS MTS/IEEE SEATTLE , , 2010 . . p.1 - - 8 . . DOI: 10.1109/OCEANS.2010.5664428 http://doi.org/10.1109/OCEANS.2010.5664428 . .

JY Chiang , , , YC Chen . . Underwater image enhancement by wavelength compensation and dehazing . . IEEE Trans Image Process , , 2012 . . 21 ( ( 4 ): ): 1756 - - 1769 . . DOI: 10.1109/TIP.2011.2179666 http://doi.org/10.1109/TIP.2011.2179666 . .

P Jr Drews , , , E do Nascimento , , , F Moraes , , , 等 . . Transmission estimation in underwater single images . . IEEE Int Conf on Computer Vision Workshops , , 2013 . . p.825 - - 830 . . DOI: 10.1109/ICCVW.2013.113 http://doi.org/10.1109/ICCVW.2013.113 . .

GD Finlayson , , , E Trezzi . . Shades of gray and colour constancy . . The 12 th Color Imaging Conf: Color Science and Engineering Systems, Technologies, Applications , , 2004 . . p.37 - - 41 . . . .

A Galdran , , , D Pardo , , , A Picón , , , 等 . . Automatic red-channel underwater image restoration . . J Vis Commun Image Represent , , 2015 . . 26 132 - - 145 . . DOI: 10.1016/j.jvcir.2014.11.006 http://doi.org/10.1016/j.jvcir.2014.11.006 . .

IJ Goodfellow , , , D Warde-Farley , , , M Mirza , , , 等 . . Maxout networks . . 2013 . . https://arxiv.org/abs/1302.4389?context=stat https://arxiv.org/abs/1302.4389?context=stat , , . .

KM He , , , J Sun , , , XO Tang . . Single image haze removal using dark channel prior . . IEEE Trans Patt Anal Mach Intell , , 2011 . . 33 ( ( 2 ): ): 2341 - - 2353 . . DOI: 10.1109/TPAMI.2010.168 http://doi.org/10.1109/TPAMI.2010.168 . .

K Iqbal , , , M Odetayo , , , A James , , , 等 . . Enhancing the low quality images using unsupervised colour correction method . . IEEE Int Conf on Systems, Man and Cybernetics , , 2010 . . p.1703 - - 1709 . . DOI: 10.1109/ICSMC.2010.5642311 http://doi.org/10.1109/ICSMC.2010.5642311 . .

Y Li , , , J Hu , , , Y Jia . . Automatic SAR image enhancement based on nonsubsampled contourlet transform and memetic algorithm . . Neurocomputing , , 2014 . . 134 70 - - 78 . . DOI: 10.1016/j.neucom.2013.03.068 http://doi.org/10.1016/j.neucom.2013.03.068 . .

BQ Mao , , , XM Jin . . Application of self-adaptive histogram equalization algorithm to image enhancement processing . . J Hebei North Univ (Nat Sci Ed) , , 2010 . . 26 ( ( 5 ): ): 64 - - 68 . . DOI: 10.3969/j.issn.1673-1492.2010.05.015 http://doi.org/10.3969/j.issn.1673-1492.2010.05.015 . .

G Padmavathi , , , P Subashini , , , MM Kumar . . Comparison of filters used for underwater image pre-processing . . Int J Comput Sci Netw Secur , , 2010 . . 10 ( ( 1 ): ): 58 - - 65 . . . .

JS Pan , , , DQ Sun , , , H Pfister , , , 等 . . Blind image deblurring using dark channel prior . . IEEE Conf on Computer Vision and Pattern Recognition , , 2016 . . p.1628 - - 1636 . . DOI: 10.1109/CVPR.2016.180 http://doi.org/10.1109/CVPR.2016.180 . .

K Panetta , , , C Gao , , , S Agaian . . Human-visual-system- inspired underwater image quality measures . . IEEE J Ocean Eng , , 2016 . . 41 ( ( 3 ): ): 541 - - 551 . . DOI: 10.1109/JOE.2015.2469915 http://doi.org/10.1109/JOE.2015.2469915 . .

YY Schechner , , , N Karpel . . Recovery of underwater visibility and structure by polarization analysis . . IEEE J Ocean Eng , , 2006 . . 30 ( ( 3 ): ): 570 - - 587 . . DOI: 10.1109/JOE.2005.850871 http://doi.org/10.1109/JOE.2005.850871 . .

CS Tan , , , A Sluzek , , , GLG Seet , , , 等 . . Range gated imaging system for underwater robotic vehicle . . OCEANS Asia Pacific , , 2007 . . p.1 - - 6 . . DOI: 10.1109/OCEANSAP.2006.4393938 http://doi.org/10.1109/OCEANSAP.2006.4393938 . .

KT Tang , , , JC Yang , , , J Wang . . Investigating haze-relevant features in a learning framework for image dehazing . . IEEE Conf on Computer Vision and Pattern Recognition , , 2014 . . p.2995 - - 3002 . . DOI: 10.1109/CVPR.2014.383 http://doi.org/10.1109/CVPR.2014.383 . .

JP Tarel , , , N Hautiere , , , L Caraffa , , , 等 . . Vision enhancement in homogeneous and heterogeneous fog . . IEEE Intell Trans Syst Mag , , 2012 . . 4 ( ( 2 ): ): 6 - - 20 . . DOI: 10.1109/MITS.2012.2189969 http://doi.org/10.1109/MITS.2012.2189969 . .

VS Thakur , , , N Tripathi . . On the way towards efficient enhancement of multi-channel underwater images . . Int J Appl Eng Res , , 2010 . . 5 ( ( 5 ): ): 895 - - 903 . . . .

C Tomasi , , , R Manduchi . . Bilateral filtering for gray and color images . . Proc 6 th Int Conf on Computer Vision , , 1998 . . p.839 - - 846 . . . .

T Treibitz , , , YY Schechner . . Active polarization descattering . . IEEE Trans Patt Anal Mach Intell , , 2009 . . 31 ( ( 3 ): ): 385 - - 399 . . DOI: 10.1109/TPAMI.2008.85 http://doi.org/10.1109/TPAMI.2008.85 . .

S Vasamsetti , , , N Mittal , , , BC Neelapu , , , 等 . . Wavelet based perspective on variational enhancement technique for underwater imagery . . Ocean Eng , , 2017 . . 141 88 - - 100 . . DOI: 10.1016/j.oceaneng.2017.06.012 http://doi.org/10.1016/j.oceaneng.2017.06.012 . .

HL Wang , , , WY Cai , , , JY Yang , , , 等 . . Design of HD video surveillance system for deep-Sea biological exploration . . Proc IEEE 16 th Int Conf on Communication Technology , , 2015 . . p.908 - - 911 . . DOI: 10.1109/ICCT.2015.7399971 http://doi.org/10.1109/ICCT.2015.7399971 . .

AP Yang , , , LY Zhang , , , C Qu , , , 等 . . Underwater images visibility improving algorithm with weighted L1 regularization . . J Electron Inform Technol , , 2017 . . 39 ( ( 3 ): ): 626 - - 633 . . DOI: 10.11999/JEIT160481 http://doi.org/10.11999/JEIT160481 . .

M Yang , , , A Sowmya . . An underwater color image quality evaluation metric . . IEEE Trans Imag Proc , , 2015 . . 24 ( ( 12 ): ): 6062 - - 6071 . . DOI: 10.1109/TIP.2015.2491020 http://doi.org/10.1109/TIP.2015.2491020 . .

SP Zhang , , , P Zeng , , , XM Luo , , , 等 . . Multi-scale retinex with color restoration and detail compensation . . J Xi'an Jiaotong Univ , , 2012 . . 46 ( ( 4 ): ): 32 - - 37 . . . .

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Recognition method for underwater communication signals that mimic dolphin whistles using phase-shifting modulation

Efficient privacy-preserving scheme for secure neural network inference

CRGT-SA: an interlaced and spatiotemporal deep learning model for network intrusion detection

Ahybrid-model optimization algorithm based on the Gaussian process and particle swarm optimization for mixed-variable CNN hyperparameter automatic search

Deep 3D reconstruction: methods, data, and challenges