A Method for Automatic Water High Light Detection and Removal in Single UAV Image

YAN Li; ZHOU Jiantong

doi:10.13203/j.whugis20170011

Volume 43 Issue 10

Oct. 2018

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2018 > 43(10): 1511-1517, 1602. > DOI: 10.13203/j.whugis20170011

YAN Li, ZHOU Jiantong. A Method for Automatic Water High Light Detection and Removal in Single UAV Image[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1511-1517, 1602. DOI: 10.13203/j.whugis20170011

Citation:

PDF (11780 KB)

A Method for Automatic Water High Light Detection and Removal in Single UAV Image

YAN Li^1,,
ZHOU Jiantong^1, ,

1.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China

Funds:

The Special Scientific Research Fund of Land and Resource Public Welfare Profession of China 201511009

More Information

Author Bio:
YAN Li, PhD, professor, specializes in the theories and methods of photogrammetry, remote sensing and LiDAR technology. E-mail: lyan@sgg.whu.edu.cn
Corresponding author:
ZHOU Jiantong, postgraduate. E-mail: ttong0202@163.com
Received Date: June 11, 2017
Published Date: October 04, 2018

Graphical Abstract

Abstract

Abstract

UAV(unmanned aerial vehicle) is convenient and low cost, water reflection can cause high light in the image and has adverse effect on UAV data processing and the DOM(digital orthophoto map) quality. We propose a method for automatic water high light detection and removal in single UAV image. Firstly, we extracted initial candidate highlight regions using multi-scale threshold detection in a high light component proposed in this paper and used the Grabcut algorithm to optimize them. Next, a decision tree was built according to the characteristics of water high light to eliminate the error detection. Then, high light regions were refined by the high light points nearby. Finally, we modified Criminisi algorithm to remove high light regions. In actual UAV images, the experimental results show that our method can remove the water high light well and is superior to other methods proposed by Mallick, Shen and Yoon in terms of PNSR(peak signal to noise ratio) and SSIM(structural similarity index) parameters and visual evaluation, and improves the DOM quality as well.
- water high light detection,
- water high light selection,
- water high light removal,
- high light component,
- improved Criminisi algorithm

FullText(HTML)

References (28)

References

[1]	Wolff L B. Using Polarization to Separate Reflection Components[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, USA, 1989
[2]	Nayar S K, Fang X S, Boult T. Separation of Reflection Components Using Color and Polarization[J].International Journal of Computer Vision, 1997, 21(3):163-186 doi: 10.1023/A:1007937815113
[3]	Lee S W, Bajcsy R.Detection of Specularity Using Colour and Multiple Views[J]. Image and Vision Computing, 1992, 10(10):643-653 doi: 10.1016/0262-8856(92)90009-R
[4]	Lin S, Li Y, Kang S B, et al.Diffuse-Specular Separation and Depth Recovery from Image Sequences[C]. European Conference on Computer Vision, Copenhagen, Denmark, 2002
[5]	Sato Y, Ikeuchi K. Temporal-Color Space Analysis of Reflection[J]. JOSA A, 1994, 11(11):2990-3002 doi: 10.1364/JOSAA.11.002990
[6]	Lin S, Shum H Y.Separation of Diffuse and Specular Reflection in Color Images[C]. IEEE Conference on Computer Vision and Pattern Recognition, Kauai, USA, 2001
[7]	Barsky S, Petrou M. The 4-Source Photometric Stereo Technique for Three-Dimensional Surfaces in the Presence of Highlights and Shadows[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(10):1239-1252 doi: 10.1109/TPAMI.2003.1233898
[8]	Shafer S A. Using Color to Separate Reflection Components[J]. Color Research & Application, 1985, 10(4):210-218 http://cn.bing.com/academic/profile?id=d572baf157d2294e171bf4070bb2d840&encoded=0&v=paper_preview&mkt=zh-cn
[9]	Klinker G J, Shafer S A, Kanade T. The Measurement of Highlights in Color Images[J]. International Journal of Computer Vision, 1988, 2(1):7-32 doi: 10.1007-BF00836279/
[10]	Bajcsy R, Lee S W, Leonardis A. Detection of Diffuse and Specular Interface Reflections and Inter-Reflections by Color Image Segmentation[J]. International Journal of Computer Vision, 1996, 17(3):241-272 doi: 10.1007/BF00128233
[11]	Tan P, Quan L, Lin S. Separation of Highlight Reflections on Textured Surfaces[C]. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, USA, 2006
[12]	Tan R T, Ikeuchi K.Separating Reflection Components of Textured Surfaces Using a Single Image[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(2):178-193 doi: 10.1109/TPAMI.2005.36
[13]	Mallick S P, Zickler T, Belhumeur P N, et al. Specu-larity Removal in Images and Videos: A PDE Approach[C]. European Conference on Computer Vision, Graz, Austria, 2006
[14]	Kim H, Jin H, Hadap S, et al.Specular Reflection Separation Using Dark Channel Prior[C]. IEEE Conference on Computer Vision and Pattern Recognition, Portland, USA, 2013
[15]	Tan R T, Ikeuchi K.Reflection Components Decomposition of Textured Surfaces Using Linear Basis Functions[C]. IEEE Conference on Computer Vision and Pattern Recognition, San Diego, USA, 2005
[16]	Suo J, An D, Ji X, et al. Fast and High Quality Highlight Removal from a Single Image[J].IEEE Transactions on Image Processing, 2016, 25(11):5441-5454 doi: 10.1109/TIP.2016.2605002
[17]	YoonK J, Choi Y, Kweon I S. Fast Separation of Reflection Components Using a Specularity-Invariant Image Representation[C]. IEEE International Conference on Image Processing, Atlanta, USA, 2006
[18]	Shen H L, Zheng Z H.Real-Time Highlight Removal Using Intensity Ratio[J]. Applied Optics, 2013, 52(19):4483-4493 doi: 10.1364/AO.52.004483
[19]	Nguyen T, Vo Q N, Kim S H, et al. A Novel and Effective Method for Specular Detection and Removal by Tensor Voting[C]. IEEE International Conference on Image Processing, Paris, France, 2014
[20]	Yu D, Han J, Jin X, et al. Efficient Highlight Removal of Metal Surfaces[J].Signal Processing, 2014, 103(10):367-379 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=JJ0232895753
[21]	Madooei A, Drew M S.Detecting Specular Highlights in Dermatological Images[C]. IEEE International Conference on Image Processing, Québec City, Canada, 2015
[22]	Munsell A H. A Color Notation[M]. Baltimore:Munsell Color Company, 1919
[23]	Rother C, Kolmogorov V, Blake A. Grabcut: Interactive Foreground Extraction Using Iterated Graph Cuts[C]. ACM Transactions on Graphics (TOG), New York, USA, 2004
[24]	Douglas D H, Peucker T K. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or Its Caricature[J].Cartographica:The International Journal for Geographic Information and Geovisualization, 1973, 10(2):112-122 doi: 10.3138/FM57-6770-U75U-7727
[25]	Cortes C, Vapnik V. Support-Vector Networks[J].Machine Learning, 1995, 20(3):273-297 http://d.old.wanfangdata.com.cn/Periodical/hwyhmb200803006
[26]	Criminisi A, Pérez P, Toyama K. Region Filling and Object Removal by Exemplar-Based Image Inpainting[J].IEEE Transactions on Image Proces-sing, 2004, 13(9):1200-1212 doi: 10.1109/TIP.2004.833105
[27]	GonzalezR C, Woods R E. Digital Image Processing[M]. 3rd ed. New Jersey:Prentice-Hall Inc, 2007
[28]	Wang Z, Bovik A C, Sheikh H R, et al. Image Quality Assessment:From Error Visibility to Structural Similarity[J].IEEE Transactions on Image Processing, 2004, 13(4):600-612 doi: 10.1109/TIP.2003.819861

[1]	YAO Yibin, RAN Qishun, ZHANG Bao. Application of Improved Heuristic Segmentation Algorithm to Step Detection of GNSS Coordinate Time Series[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 648-654. DOI: 10.13203/j.whugis20170322
[2]	SHEN Xin, LIU Yulin, LI Shixue, YAO Huang. An Optimization Design Method for High Temporal Resolution Remote Sensing Satellite Constellation Based on Improved PSO Algorithm[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 1986-1993. DOI: 10.13203/j.whugis20180160
[3]	Zhan Weiwei, Wang Wei, Chen Nengcheng, Wang Chao. Path Planning Strategies for UAV Based on Improved A*Algorithm[J]. Geomatics and Information Science of Wuhan University, 2015, 40(3): 315-320.
[4]	ZHA Feng, XU Jiangning, LI Jingshu, HE Hongyang. Improvement of a Series of Fuzzy Damp Algorithms in SINS[J]. Geomatics and Information Science of Wuhan University, 2013, 38(6): 705-709.
[5]	ZHAN Jianfeng, FAN Chong, LI Tao. A Forest Firespot Automatic Detection Algorithm for HJ-IRS Imagery[J]. Geomatics and Information Science of Wuhan University, 2012, 37(11): 1321-1324.
[6]	LUO Zhicai, LIN Xu, ZHOU Boyang. Improved Algorithm of Autocovariance Least-Squares Noise Estimation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(10): 1164-1167.
[7]	LI Zhenhai, LUO Zhicai, WANG Haihong, LI Qiong. Visualization of Gravity Vector Field Using Improved FLIC Algorithm[J]. Geomatics and Information Science of Wuhan University, 2011, 36(3): 276-279.
[8]	YIN Shuling, SHU Ning, LIU Xinhua. Classification of Remote Sensing Image Based on Adaptive GA and Improved BP Algorithm[J]. Geomatics and Information Science of Wuhan University, 2007, 32(3): 201-204.
[9]	YAO Huanmei, HUANG Rentao, GAN Fuxing, LIU Yang. Principal Component Analysis of the Water Quality Evaluation in East Lake[J]. Geomatics and Information Science of Wuhan University, 2005, 30(8): 732-735.
[10]	CHEN Jiangping, FU Zhongliang, XU Zhihong. An Improved Algorithm of Apriori[J]. Geomatics and Information Science of Wuhan University, 2003, 28(1): 94-99.

Cited By

Cited by

Periodical cited type(3)

1.	袁东，张健，余洋洋，张志良. 差异特征注意力引导的偏振图像高光移除. 光学技术. 2024(02): 247-256 .
2.	陈毅夫，何敬，刘刚，毛佳琪. 融合Swin-Transformer网络模型的水体高光区域提取. 遥感信息. 2023(04): 129-136 .
3.	乔玉晶，张思远，赵宇航. 高光弱纹理物体表面鲁棒重建方法. 光子学报. 2019(12): 172-182 .

Other cited types(2)

Get Citation

PDF

XML

Article views (1719) PDF downloads (252) Cited by(5)

A Method for Automatic Water High Light Detection and Removal in Single UAV Image

Abstract

References

Related Articles

Cited by

Periodical cited type(3)

Other cited types(2)

Catalog

Related

A Method for Automatic Water High Light Detection and Removal in Single UAV Image

Abstract

References

Related Articles

Cited by

Periodical cited type(3)

Other cited types(2)

Catalog

Related

Export File

Citation

Format

Content