Fused Image Quality Assessment Based on Human Visual Characteristics

XU Lina; XIAO Qi; HE Luxiao

doi:10.13203/j.whugis20170168

Volume 44 Issue 4

Apr. 2019

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2019 > 44(4): 546-554. > DOI: 10.13203/j.whugis20170168

XU Lina, XIAO Qi, HE Luxiao. Fused Image Quality Assessment Based on Human Visual Characteristics[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 546-554. DOI: 10.13203/j.whugis20170168

Citation:

PDF (24214 KB)

Fused Image Quality Assessment Based on Human Visual Characteristics

Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China

Funds:

The National Natural Science Foundation of China 61601418

More Information

Author Bio:
XU Lina, PhD, associate professor, majors in high-resolution remote sensing image processing and application. E-mail:silvaxu@sina.com
Received Date: August 15, 2018
Published Date: April 04, 2019

Graphical Abstract

Abstract

Abstract

Image quality assessment plays an important role in remote sensing image fusion. Research on objective evaluation methods is of great value in this field. Because the fused images will be observed by human finally, the best objective evaluation index of image quality should be consistent with the subjective evaluation. After the human visual characteristics are introduced into, image quality evaluation method can get better result. Therefore, based on the multi channels decomposition and contrast sensitivity characteristics of human visual system, this paper proposes a new method to evaluate the fusion quality of panchromatic image and multispectral image. Firstly, the color distortion and structural similarity are modified to evaluate the spectral information and spatial information respectively. Secondly, they are integrated as the overall evaluation of fused image. According to the experiment evaluating quality of different fused images by SPOT image data and GF-2 image data, it proves that the proposed method is in good agreement with the subjective evaluation when the remote sensing image is high resolution data.

FullText(HTML)

References (24)

References

[1]	PohI C, van Gend'eren J L. Multisensor Image Fusion in Remote Sensing: Concepts, Methods and Application[J]. International Journal of Remote Sensing, 1998, 19(5): 823-854 doi: 10.1080/014311698215748
[2]	韩玲.多源遥感信息融合技术及多源信息在地学中的应用研究[D].西安: 西北大学, 2005 Han Ling. Study of Multi-source Remote Sensing Image Fusion Technology and Multi-source Information's Application to Geoscience[D]. Xi'an: Northwest University, 2005
[3]	马旭东.光学遥感影像压缩及融合的质量评价研究[D].武汉: 武汉大学, 2014 Ma Xudong. Research on Quality Assessment of Image Compression and Image Fusion for Optical Remote Sensing Image[D]. Wuhan: Wuhan University, 2014
[4]	李艳芳, 程新文, 金彪, 等.几种常见影像融合方法的比较[J].地理信息系统, 2009, 7(4):102-105 http://d.old.wanfangdata.com.cn/Periodical/dlkjxx200902036 Li Yanfang, Cheng Xinwen, Jin Biao, et al. Comparison of Several Common Image Fusion Methods[J]. Geospatial Information, 2009, 7(4): 102-105 http://d.old.wanfangdata.com.cn/Periodical/dlkjxx200902036
[5]	Maria G A, Jose L S, Raguel G C, et al. Fusion of Multispectral and Panchromatic Images Using Improved HIS and PCA Mergers Based on Wavelet Decomposition[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 42(6): 1291-1299 doi: 10.1109-TGRS.2004.825593/
[6]	邢帅.多源遥感影像配准与融合技术的研究[D].郑州: 信息工程大学, 2004 Xing Shuai. Research on Image Registration and Image Fusion for Multi-sensors Remote Sensing Image[D]. Zhengzhou: Information Engineering University, 2004
[7]	王智均, 李德仁, 李清泉.多进制小波理论在SPOT和TM影像融合中的应用[J].武汉大学学报·信息科学版, 2001, 26(1):24-28 http://ch.whu.edu.cn/CN/abstract/abstract5033.shtml Wang Zhijun, Li Deren, Li Qingquan. Fusion of SPOT-P and TM Multispectral Image by M-band Wavelet Theory[J]. Geomatics and Information Science of Wuhan University, 2001, 26(1): 24-28 http://ch.whu.edu.cn/CN/abstract/abstract5033.shtml
[8]	闫利, 岳昔娟, 崔晨风.一种定量确定遥感融合图像空间分辨率的方法[J].武汉大学学报·信息科学版, 2007, 32(8):667-670 http://ch.whu.edu.cn/CN/abstract/abstract1952.shtml Yan Li, Yue Xijuan, Cui Chenfeng. A Method to Quantitatively Determine Spatial Resolution of RS Fused Image[J]. Geomatics and Information Science of Wuhan University, 2007, 32(8): 667-670 http://ch.whu.edu.cn/CN/abstract/abstract1952.shtml
[9]	Daly S J. The Visible Difference Predictor: An Algorithm for the Assessment of Image Fidelity[J]. Digital Image and Human Vision, 1993, 1666: 179-206 doi: 10.1117-12.135952/
[10]	Lubin J. A Visual Discrimination Model for Image System Design and Evaluation[OL]. https://doi.org/10.1142/9789812831200_0010,1995
[11]	Wang Z, Bovik A C, Sheikh H R. et al. Image Quality Assessment: From Error Visibility to Structural Similarity[J]. IEEE Trans Image Processing, 2004, 13(4): 600-612 doi: 10.1109/TIP.2003.819861
[12]	Wang Z, Bovik A C, Lu L. Why Is Image Quality Assessment so Difficult[C]. IEEE Int Conf Acoust Speech and Signal Processing, Orlando, FL, USA, 2002
[13]	Aja-Fernandez S, Estepar R S J, Westin C F, et al. Image Quality Assessment Based on Local Variance[C]. The 28th IEEE EMBS Annual International Conference, New York, USA, 2006
[14]	马旭东, 闫利, 曹纬, 等.一种新的利用梯度信息的图像质量评价模型[J].武汉大学学报·信息科学版, 2014, 39(12):1412-1418 http://ch.whu.edu.cn/CN/abstract/abstract3133.shtml Ma Xudong, Yan Li, Cao Wei, et al. A New Image Quality Assessment Mode Based on the Gradient Information[J]. Geomatics and Information Science of Wuhan University, 2014, 39(12): 1412-1418 http://ch.whu.edu.cn/CN/abstract/abstract3133.shtml
[15]	刘军, 邵振峰.基于特征结构相似度的遥感影像融合质量评价指标[J].光子学报, 2011, 40(1): 126-131 http://d.old.wanfangdata.com.cn/Periodical/gzxb201101027 Liu Jun, Shao Zhenfeng. Feature-Based Remote Sensing Image Fusion Quality Metrics Using Structure Similarity[J]. Acta Photonica Sinica, 2011, 40(1): 126-131 http://d.old.wanfangdata.com.cn/Periodical/gzxb201101027
[16]	刘书琴, 毋立芳, 宫玉, 等.图像质量评价综述[J].中国科技论文在线, 2011, 6(7): 501-506 doi: 10.3969/j.issn.2095-2783.2011.07.006 Liu Shuqin, Wu Lifang, Gong Yu, et al. Overview of Image Quality Assessment[J]. Sciencepaper Online, 2011, 6(7): 501-506 doi: 10.3969/j.issn.2095-2783.2011.07.006
[17]	Carper W J. The Use of Intensity-Huesaturation Transformations for Merging SPOT Panchromatic and Multispectral Image Data[J]. Photogrammetric Engineering and Remote Sensing, 1990, 56(4): 459-467
[18]	刘宇琼.基于像素级多源遥感影像融合技术的研究[D].西安: 长安大学, 2007 Liu Yuqiong. Study on Pixel-Level Multi-source Remote Sensing Data Fusion Technique[D]. Xi'an: Chang'an University, 2007
[19]	Mallat S G. A Theory for Multi-resolution Signal Decomposition: The Wavelet Representation[J]. IEEE Transation PAMI, 1989, 11(7): 674-693 doi: 10.1109/34.192463
[20]	王正友, 黄隆华.基于对比度敏感度的图像质量评价方法[J].计算机应用, 2006, 26(8): 1857-1859 http://d.old.wanfangdata.com.cn/Periodical/jsjyy200608032 Wang Zhengyou, Huang Longhua. Image Quality Assessment Method Based on Contrast Sensitivity[J]. Computer Application, 2006, 26(8): 1857-1859 http://d.old.wanfangdata.com.cn/Periodical/jsjyy200608032
[21]	Shen J H. On the Foundations of Vision Modeling Ⅰ. Weber's Law and Weberized TV Restoration[J]. Physica D Nonlinear Phenomena, 2003, 175(3): 241-251
[22]	Mannos J L, Sakrison D J. The Effects of a Visual Fidelity Criterion on the Encoding of Images[J]. IEEE Trans Information Theory, 1974, 4:525-536
[23]	胡许明, 张登福, 南栋, 等.基于人眼视觉特征的图像视觉质量评价方法[J].计算机应用, 2012, 32(7):1882-1884, 1889 http://cdmd.cnki.com.cn/Article/CDMD-10358-1014299853.htm Hu Xuming, Zhang Dengfu, Nan Dong, et al. Method of Image Visual Quality Evaluation Based on Human Visual Characteristics[J]. Computer Application, 2012, 32(7): 1882- 1884, 1889 http://cdmd.cnki.com.cn/Article/CDMD-10358-1014299853.htm
[24]	李文娟.基于视觉特性的彩色图像质量评估研究[D].长春: 吉林大学, 2006 Li Wenjuan. Study on the Algorithms for HVS-Based Color Image Measurement[D]. Changchun: Jilin University, 2006

[1]	ZHU Shaolin, YUE Dongjie, HE Lina, CHEN Jian, LIU Shengnan. BDS-2/BDS-3 Joint Triple-Frequency Precise Point Positioning Models and Bias Characteristic Analysis[J]. Geomatics and Information Science of Wuhan University, 2023, 48(12): 2049-2059. DOI: 10.13203/j.whugis20210273
[2]	LIU Zhiqiang, YUE Dongjie, WANG Hu, ZHENG Dehua. An Approach for Real-Time GPS/GLONASS Satellite Clock Estimation with GLONASS Code Inter-Frequency Biases Compensation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1209-1215. DOI: 10.13203/j.whugis20150542
[3]	RUAN Rengui, WU Xianbing, FENG Laiping. Comparison of Observation Models and Ionospheric Elimination Approaches for Single Frequency Precise Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2013, 38(9): 1023-1028.
[4]	ZOU Xuan, JIANG Weiping, SU Lina, LIU Jingnan. A New Single-Frequency PPP Method Using Dynamic Reference Network[J]. Geomatics and Information Science of Wuhan University, 2013, 38(4): 403-407.
[5]	TU Rui, HUANG Guanwen, ZHANG Qin, WANG Li. PPP Algorithm of Single Frequency Based on Corrections of Single-base Station and Ionospheric Parameters Estimation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(2): 170-173.
[6]	TU Rui, HUANG Guanwen, ZHANG Qin, WANG Li. The Research of Dual Frequency Solution Method for Single Frequency Precise Point Positioning(PPP) Based on SEID Model[J]. Geomatics and Information Science of Wuhan University, 2011, 36(10): 1187-1190.
[7]	SHI Chuang, GU Shengfeng, GENG Changjiang, SONG Weiwei. High-Precision Single-Frequency Point Positioning with Randomness of Ionosphere Delay Correction in Consideration[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 807-810.
[8]	LIU Jihua, OU Jikun, SUN Baoqi, ZHONG Shiming. The GEO Satellite Precise Orbit Determination Based on Inter-satellite Single Difference Method[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 24-28.
[9]	SONG Weiwei, SHI Chuang, YAO Yibin, YE Shirong. Ionosphere Delay Processing Methods and Positioning Precision of Single Frequency Precise Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2009, 34(7): 778-781.
[10]	ZHANG Xiaohong, LI Xingxing, GUO Fei, ZHANG Ming. Realization and Precision Analysis of Single-Frequency Precise Point Positioning Software[J]. Geomatics and Information Science of Wuhan University, 2008, 33(8): 783-787.

Cited By

Cited by

Periodical cited type(11)

1.	段博文，白征东，郭锦萍. 北斗二号卫星伪距偏差分析与建模. 测绘工程. 2024(02): 18-27 .
2.	高扬，沙海，楚恒林，王梦丽. 北斗B1C、B2a信号非理想性分析及接收约束建议. 武汉大学学报(信息科学版). 2023(04): 587-592 .
3.	耿涛，李钟兴，谢新，马壮，赵齐乐. GNSS接收机伪距偏差确定方法及其对定位的影响. 武汉大学学报(信息科学版). 2023(07): 1134-1145 .
4.	周中华，万祥，程艳，刘志忠，汪文君，张雪丽. 一种地基GNSS接收机差分码偏差估算方法. 空间科学学报. 2022(01): 170-178 .
5.	许海林，周恩泽，童梦想，鄂盛龙，田翔，罗颖婷. GPS/BDS/Galileo单点定位精度分析. 测绘地理信息. 2022(04): 19-24 .
6.	李浩东，赵齐乐，陶钧，龙宇浩. 北斗三号卫星FCB估计及其模糊度固定. 武汉大学学报(信息科学版). 2022(09): 1439-1446 .
7.	慕仁海，党亚民，许长辉. BDS-3新频点单点定位研究. 测绘通报. 2021(03): 12-17 .
8.	毛飞宇，龚晓鹏，辜声峰，王琛琛，楼益栋. 北斗三号卫星导航信号接收机端伪距偏差建模与验证. 测绘学报. 2021(04): 457-465 .
9.	徐宗秋，丁新展，徐彦田，唐龙江，李磊，胡艳阳. BDS静态精密单点定位模糊度固定解精度分析. 测绘科学. 2019(07): 30-34 .
10.	李森，周命端，陈积旭. 北斗数据工程控制网应用实验及精度分析. 测绘科学. 2019(09): 1-6 .
11.	唐卫明，刘前，高柯夫，邓辰龙，崔健慧，沈明星. 北斗伪距码偏差对基线解算的影响分析. 武汉大学学报(信息科学版). 2018(08): 1199-1206 .

Other cited types(13)

Get Citation

PDF

XML

Article views PDF downloads Cited by(24)

Fused Image Quality Assessment Based on Human Visual Characteristics

Abstract

References

Related Articles

Cited by

Periodical cited type(11)

Other cited types(13)

Catalog

Related

Fused Image Quality Assessment Based on Human Visual Characteristics

Abstract

References

Related Articles

Cited by

Periodical cited type(11)

Other cited types(13)

Catalog

Related

Export File

Citation

Format

Content