全局参数估计的水下目标偏振复原方法

范之国; 宋强; 代晴晴; 闫羽

doi:10.3788/OPE.20182607.1621

您当前的位置：

首页 >

文章列表页 >

全局参数估计的水下目标偏振复原方法

现代应用光学 | 更新时间：2020-08-13

- 全局参数估计的水下目标偏振复原方法
- Underwater target polarization recovery method based on global parameter estimation
- 光学精密工程 2018年26卷第7期页码：1621-1632
- 作者机构：
  
  合肥工业大学计算机与信息学院, 安徽合肥 230061
- 作者简介：
  
  [ "范之国(1979-), 男, 安徽霍山人, 博士, 副教授, 硕士生导师, 2002年于辽宁科技大学获得学士学位, 2007年、2011年于合肥工业大学分别获得硕士、博士学位, 主要从事偏振光学探测及偏振光导航方面的研究。E-mail:fzghfut@163.com" ]
  [ "宋强(1992-), 男, 安徽长丰人, 硕士研究生, 2015年于安徽工业大学获得学士学位, 主要从事偏振光学探测及水下偏振光学成像方面的研究。E-mail:1522108669@qq.com" ]
- 基金信息：
  
  国家自然科学基金资助项目(61571177);国家自然科学基金资助项目(6157117);装备预研教育部联合基金资助项目(6141A02022609)
- DOI：10.3788/OPE.20182607.1621
  中图分类号： TP391
- 收稿日期：2017-12-19，
  
  录用日期：2018-2-10，
  
  纸质出版日期：2018-07-25
- 稿件说明：
移动端阅览
范之国, 宋强, 代晴晴, 等. 全局参数估计的水下目标偏振复原方法[J]. 光学精密工程, 2018,26(7):1621-1632.

Zhi-guo FAN, Qiang SONG, Qing-qing DAI, et al. Underwater target polarization recovery method based on global parameter estimation[J]. Optics and precision engineering, 2018, 26(7): 1621-1632.
范之国, 宋强, 代晴晴, 等. 全局参数估计的水下目标偏振复原方法[J]. 光学精密工程, 2018,26(7):1621-1632. DOI： 10.3788/OPE.20182607.1621.

Zhi-guo FAN, Qiang SONG, Qing-qing DAI, et al. Underwater target polarization recovery method based on global parameter estimation[J]. Optics and precision engineering, 2018, 26(7): 1621-1632. DOI： 10.3788/OPE.20182607.1621.

摘要

水体介质对光的吸收和散射是导致水下成像退化的两大主要影响因素。针对水下目标成像，本文提出了一种全局参数估计的水下目标偏振复原方法，利用构建的精简水下目标偏振重构模型，通过自动估计全局最优偏振信息重构参数，复原出水下目标图像，降低水体对图像质量的影响。在估计重构参数的过程中，首先，采用偏振中值滤波方法和基于亮原色原理的方法，分别估算水下背景光偏振度信息和无穷远处水下背景光强值；再利用基于最小互信息原则对估计的背景光偏振度信息进行优化；然后采用水下目标偏振图像增强算法将得到的水下目标重构图进行细节增强处理，最终获得复原后的水下目标辐射信息图。实验结果表明，在性能评价指标方面，相较于水下原图和其他水下复原方法处理图，利用本文方法处理后所得的图像增强测量值EME平均提高了120%，图像质量得到了明显的改善。该方法解决了人工取景估计参数不佳的问题，提高了复原目标图像的对比度，可以用于浑浊水下的目标探测与识别。

Abstract

The absorption and scattering of underwater light by water are the two main factors influencing image degradation. With a focus on underwater target imaging

this paper proposes an underwater target polarization recovery method by global parameter estimation

using a simplified underwater target polarization reconstruction model

which recovers an underwater target image by automatically estimating global optimal polarization information reconstruction parameters to reduce the impact of the medium on image quality. First

a polarization median filter method and the bright primary principle method were used to estimate the underwater background light polarization degree information and the infinite underwater background light intensity values

respectively. Based on the principle of minimum mutual information

the background light polarization degree information was optimized and estimated. Then

adopting the underwater target polarization image enhancement algorithms to enhance the details of the underwater reconstruction target

a clear figure of the underwater target's radiation information was produced. The experimental results show that the value of the measure of enhancement (EME) in the suggested method increased by 120% on average

compared with the original strength of the figure and that of other underwater recovery methods for the calculation of the performance evaluation index. Further

the image quality was significantly improved. The method has solved the inaccuracy problem while estimating parameters via artificial view and improved the contrast of the restored target image. The method can be used to detect and identify turbid underwater targets.

关键词

Keywords

references

郭继昌, 李重仪, 郭春乐, 等.水下图像增强和复原方法研究进展[J].中国图象图形学报, 2017, 22(3):273-287.

GUO J CH, LI CH Y, GUO CH L, et al .. Research progress of underwater image enhancement and restoration methods[J]. Journal of Image and Graphics , 2017, 22(3):273-287.(in Chinese)

JI T T, WANG J Y. An approach to underwater image enhancement based on image structural decomposition[J]. Journal of Ocean of China , 2015, 14(2):255-260.

LI C Y, GUO J C. Underwater image enhancement by dehazing and color correction[J]. Journal of Electronic Imaging , 2015, 24(3):033023.

JIN W Q, CAO F M, WANG X, et al .. Rang gated underwater laser imaging system based on intensified gate imaging technology[J]. SPIE , 2008:6621.

LI L, ZHANG SH J. A survey on algorithms of nonnegative matrix factorization[J]. Acta Electronica Sinica , 2008, 36(4):737-743.

XIANG Q, YANG K, YU L, et al .. Reflective underwater ghost imaging[J] . Acta Optica Sinica . 2015, 35(7):0711002.

SCHECHNER Y Y, KARPEL N. Recovery of underwater visibility and structure by polarization analysis[J]. IEEE Journal of Oceanic Engineering , 2005, 30(3):570-587.

SCHECHNER Y Y, KARPEL N. Clear underwater vision[C]. IEEE Conference on Computer Vision and Pattern Recognition , 2004, 1: I-I.

HUANG B J, LIU T G, HU H F, et al .. Underwater image recovery considering polarization effects of objects[J]. Optics Express , 2016, 24(9):9826-9838.

SCHECHNER Y Y, TREIBITZ T. Active polarization descattering[J]. IEEE Trans. Pattern Anal. Mach. Intell ., 2009, 31:385-399.

吴斌, 付辉, 张红英.大气光幂雾图像的清晰度复原[J].光学精密工程, 2016, 24(8):2018-2026.

WU B, FU H, ZHANG H Y. De-hazing of atmosphere veil haze images[J]. Opt. Precision Eng ., 2016, 24(8):2018-2026. (in Chinese)

朱攀, 刘泽阳, 黄战华.基于DTCWT和稀疏表示的红外偏振与光强图像融合[J].光子学报, 2017, 46(12):1210002.

ZHU P, LIU Z Y, HUANG ZH H. Infrared polarization and intensity image fusion based on dual-tree complex wavelet transform and sparse representation[J]. Acta Photonica Sinica , 2017, 46(12):1210002.(in Chinese)

王卫星, 肖翔, 陈良琴.结合最小滤波和引导滤波的暗原色去雾[J].光学精密工程, 2015, 23(7):2100-2108.

WANG W X, XIAO X, CHEN L Q. Image dark channel prior haze removal based on minimum filtering and guided filtering[J]. Opt. Precision Eng ., 2015, 23(7):2100-2108. (in Chinese)

FU X, LIN Q, GUO W. Single image de-haze under non-uniform illumination using bright channel prior[J]. Journal of Theoretical & Applied Information Technology , 2013, 48(3):1843-1848.

怀宇, 范之国, 孙洁, 等.三通棱镜同时偏振测量系统的标定[J].光电工程, 2015, 42(11):18-24.

HUAI Y, FAN ZH G, SUN J, et al .. Calibration of the three links prism simultaneous polarization measurement system[J]. Opto-Electronic Engineering , 2015, 42(11):18-24. (in Chinese)

孙洁, 高隽, 怀宇, 等.全天域大气偏振模式的实时测量系统[J].光电工程, 2016, 43(9):45-50.

SUN J, GAO J, HUAI Y, et al .. Real-time measurement system for the pattern of all skylight polarization[J]. Opto-Electronic Engineering , 2016, 43(9):45-50. (in Chinese)

HAN P, LIU F, YANG K, et al .. Active underwater descattering and image recovery[J]. Applied Optics , 2017, 56(23):6631.

BICKEL W S, VIDEEN G W. Polarized light scattering applications and measurements of fundamental systems[J]. SPIE , 1994, 1746:14-21.

MANTIUK R, KIM K J, REMPEL A G, et al .. HDR-VDP-2:A calibrated visual metric for visibility and quality predictions in all luminance conditions[J]. ACM Transactions on Graphics , 2011, 30(4):40.

YANG M, SOWMYA A. New image quality evaluation metric for underwater video[J]. IEEE Signal Letters , 2014, 21(10):1215-1219.

AGAIAN S S, PANETTA K, GRIGORYAN A M. Transform-based image enhancement algorithms with performance measure[J]. IEEE Trans. Image Process , 2001, 10(3):367-382.

浏览量

244

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

电力巡检中的偏振图像特征融合

面向机翼线缆支架的装配符合性视觉检测

基于无监督学习和注意力机制的水下偏振图像融合

基于偏振信息的海面太阳耀光抑制

基于动态视觉传感器的旋转检偏成像系统