Image and Sensor Fusion -- Review and Survey Articles, Evaluations

Chapter Contents (Back)
Survey, Sensor Fusion. Sensor Fusion. Fusion.

Mitiche, A., and Aggarwal, J.K.,
Multiple Sensor Integration/Fusion through Image Processing: A Review,
OptEng(25), No. 3, March 1986, pp. 380-386. Sensor Fusion. A review of some of what is being done at UT regarding the use of visible and thermal or range data. BibRef 8603

Bloch, I.,
Information Combination Operators for Data Fusion: A Comparative Review with Classification,
SMC-A(26), No. 1, January 1996, pp. 52-67.
IEEE Top Reference. Survey, Data Fusion. BibRef 9601

Murphy, R.R.,
Biological and Cognitive Foundations of Intelligent Sensor Fusion,
SMC-A(26), No. 1, January 1996, pp. 42-51.
IEEE Top Reference. BibRef 9601

Dasarathy, B.V.,
Sensor Fusion 1997,
OptEng(36), No. 3, March 1997, pp. 629-631. 9704
Sensor Fusion 1996,
OptEng(35), No. 3, March 1996, pp. 601-602. Special Section Guest Editorial. BibRef

Varshney, P.K.,
Special Issue on Data Fusion,
PIEEE(85), No. 1, January 1997, pp. 3-5. 9701

Varshney, P.K.,
Multisensor Data Fusion,
ECEJ(9), No. 6, December 1997, pp. 245-253. 9801

Hall, D.L., Llinas, J.,
An Introduction To Multisensor Data Fusion,
PIEEE(85), No. 1, January 1997, pp. 6-23. 9701

Brady, J.M.,
Special Issue on Sensor Data Fusion,
IJRR(7), No. 6, 1989, pp. 1-161. BibRef 8900

Zhang, Z.[Zhong], Blum, R.S.,
A Categorization of Multiscale-Decomposition-Based Image Fusion Schemes with a Performance Study for a Digital Camera Application,
PIEEE(87), No. 8, August 1999, pp. 1315-1326.
IEEE DOI BibRef 9908

Hall, D.L.[David L.], Linas, J.[James],
Handbook of Multisensor Data Fusion,
CRC PressMay 2001, ISBN 0-8493-2379-7. BibRef 0105

Wang, Z., Ziou, D., Armenakis, C., Li, D., Li, Q.,
A Comparative Analysis of Image Fusion Methods,
GeoRS(43), No. 6, June 2005, pp. 1391-1402.
IEEE Abstract. 0506

CVonline: Sensor Fusion, Registration and Planning,
CV-OnlineJuly 2001.
HTML Version. Survey, Fusion. Survey, Registration. BibRef 0107

Pajares, G.[Gonzalo], Manuel de la Cruz, J.[Jesus],
A wavelet-based image fusion tutorial,
PR(37), No. 9, September 2004, pp. 1855-1872.
Elsevier DOI 0407
Survey, Image Fusion. multiscale-decomposition (
See also Categorization of Multiscale-Decomposition-Based Image Fusion Schemes with a Performance Study for a Digital Camera Application, A. ) Wavelet:
See also Multisensor Image Fusion Using the Wavelet Transform. ARSIS.
See also Image fusion: The ARSIS concept and some successful implementation schemes. BibRef

Dixon, T.D.[Timothy D.], Canga, E.F.[Eduardo Fernández], Nikolov, S.G.[Stavri G.], Troscianko, T.[Tom], Noyes, J.M.[Jan M.], Canagarajah, C.N.[C. Nishan], Bull, D.R.[Dave R.],
Selection of image fusion quality measures: Objective, subjective, and metric assessment,
JOSA-A(24), No. 12, December 2007, pp. B125-B135.
WWW Link. 0801

Liu, Z.[Zheng], Forsyth, D.S.[David S.], Laganiere, R.[Robert],
A feature-based metric for the quantitative evaluation of pixel-level image fusion,
CVIU(109), No. 1, January 2008, pp. 56-68.
Elsevier DOI 0801
Feature measurement; Image fusion; Image quality; Phase congruency; Cross-correlation BibRef

Liu, Z.[Zheng], Blasch, E.[Erik], Xue, Z.Y.[Zhi-Yun], Zhao, J.Y.[Ji-Ying], Laganiere, R.[Robert], Wu, W.[Wei],
Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study,
PAMI(34), No. 1, January 2012, pp. 94-109.
Survey, Inage Fusion. Study 12 fusion metrics and images with distortion. Analysis can be applied to other sets of metrics, etc. BibRef

Piella, G.[Gemma],
Image Fusion for Enhanced Visualization: A Variational Approach,
IJCV(83), No. 1, June 2009, pp. xx-yy.
Springer DOI 0903
Fuse multiple images, preserve information and enhance contrast. BibRef

Piella, G., Heijmans, H.J.A.M.,
A new quality metric for image fusion,
ICIP03(III: 173-176).

Bloch, I.[Isabelle],
Information Fusion in Signal and Image Processing,
Wiley-ISTEJanuary 2008. ISBN: 978-1-84821-019-6.
HTML Version. Buy this book: Information Fusion in Signal and Image Processing (Digital Signal and Image Processing) 0905

Zhang, H.K.[Hankui K.], Huang, B.[Bo],
A New Look at Image Fusion Methods from a Bayesian Perspective,
RS(7), No. 6, 2015, pp. 6828.
DOI Link 1507

Pistonesi, S.[Silvina], Martinez, J.[Jorge], Ojeda, S.M.[Silvia Maria], Vallejos, R.[Ronny],
Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms,
IPOL(8), 2018, pp. 345-368.
DOI Link 1811
Code, Fusion. Code, Fusion, Matlab. BibRef

Zhang, X.C.[Xing-Chen],
Deep Learning-Based Multi-Focus Image Fusion: A Survey and a Comparative Study,
PAMI(44), No. 9, September 2022, pp. 4819-4838.
Image fusion, Deep learning, Frequency modulation, Transforms, Generative adversarial networks, Visualization, Task analysis, mage processing BibRef

Sun, Q.H.[Qian-Hui], Yang, Q.Y.[Qing-Yu], Li, C.Y.[Chong-Yi], Zhou, S.C.[Shang-Chen], Feng, R.C.[Rui-Cheng], Dai, Y.K.[Yue-Kun], Sun, W.X.[Wen-Xiu], Zhu, Q.P.[Qing-Peng], Loy, C.C.[Chen Change], Gu, J.[Jinwei], Yu, H.Y.[Hong-Yuan], Liu, Y.Q.[Yu-Qing], Yu, W.C.[Wei-Chen], Ge, L.[Lin], Zhang, X.L.[Xiao-Lin], Jia, Q.[Qi], Zhang, H.[Heng], Yin, X.[Xuanwu], Zuo, K.[Kunlong], Wu, Q.[Qi], Lin, W.J.[Wen-Jie], Jiang, T.[Ting], Jiang, C.Z.[Cheng-Zhi], Han, M.Y.[Ming-Yan], Li, X.P.[Xin-Peng], Luo, J.[Jinting], Yu, L.[Lei], Fan, H.Q.[Hao-Qiang], Liu, S.C.[Shuai-Cheng], Wang, K.Y.[Kun-Yu], Cao, C.Z.[Cheng-Zhi], Guan, Y.[Yuanshen], Xia, J.Y.[Ji-Yuan], Xu, R.[Ruikang], Yao, M.[Mingde], Xiong, Z.W.[Zhi-Wei],
MIPI 2023 Challenge on RGBW Fusion: Methods and Results,

Yang, Q.Y.[Qing-Yu], Yang, G.[Guang], Jiang, J.[Jun], Li, C.Y.[Chong-Yi], Feng, R.C.[Rui-Cheng], Zhou, S.C.[Shang-Chen], Sun, W.X.[Wen-Xiu], Zhu, Q.[Qingpeng], Loy, C.C.[Chen Change], Gu, J.[Jinwei], Wang, Z.[Zhen], Li, D.[Daoyu], Zhang, Y.Z.[Yu-Zhe], Peng, L.[Lintao], Chang, X.Y.[Xu-Yang], Zhang, Y.[Yinuo], Bian, L.[Liheng], Li, B.[Bing], Huang, J.[Jie], Yao, M.[Mingde], Xu, R.K.[Rui-Kang], Zhao, F.[Feng], Liu, X.H.[Xiao-Hui], Xu, R.J.[Rong-Jian], Zhang, Z.[Zhilu], Wu, X.H.[Xiao-He], Wang, R.[Ruohao], Li, J.[Junyi], Zuo, W.M.[Wang-Meng], Jia, Z.[Zhuang], Lee, D.[DongJae], Jiang, T.[Ting], Wu, Q.[Qi], Jiang, C.Z.[Cheng-Zhi], Han, M.Y.[Ming-Yan], Li, X.P.[Xin-Peng], Lin, W.J.[Wen-Jie], Li, Y.[Youwei], Fan, H.Q.[Hao-Qiang], Liu, S.C.[Shuai-Cheng],
MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report,
Springer DOI 2304

Zhang, X.S.[Xi-Shan], Gao, K.[Ke], Zhang, Y.D.[Yong-Dong], Zhang, D.M.[Dong-Ming], Li, J.T.[Jin-Tao], Tian, Q.[Qi],
Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description,
Adaptation models, Artificial neural networks, Decoding, Dynamics, Feature extraction, Visualization BibRef

Han, Z., Tang, X., Gao, X., Hu, F.,
Image Fusion and Image Quality Assessment of Fused Images,
DOI Link 1311

Revuelta-Martínez, A., García-Varea, I., Puerta, J.M., Rodríguez, L.,
ISDM at ImageCLEF 2010 Fusion Task,
Springer DOI 1008

Engle, M., Sarkani, S., Mazzuchi, T.,
Technical maturity evaluations for sensor fusion technologies,

Zou, M.Y.[Mou-Yan], Liu, Y.[Yan],
Multi-Sensor Image Fusion: Difficulties and Key Techniques,

Blasch, E.[Erik],
Emerging Trends in Persistent Surveillance Information Fusion,

Wang, Q.A.[Qi-Ang], Shen, Y.[Yi],
Performance Assessment of Image Fusion,
Springer DOI 0612

Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Multi-Focus Fusion, Multi-Focal Fusion .

Last update:Dec 8, 2023 at 20:54:15