Objective image fusion evaluation method for target recognition based on target quality factor
Tóm tắt
A novel objective evaluation method for image fusion based on target quality factor is proposed from the point of view of target recognition. Three-component indicators named preservation degree of special features of the target, target edge quality and interference edge suppression ratio are defined. These component indicators can evaluate the quality of the target from three different aspects. Preservation degree of special features of the target quantitatively describes the preservation degree of special features in the fusion image, which are very important for target recognition in the special source images. Target edge quality is used to evaluate the integrity and quality of the boundary information contained in the fusion image. Interference edge suppression ratio quantitatively describes the boundary information whether the fusion image will produce confusion. Target quality factor is obtained by weighted averaging of these component indicators. The experimental results show that the target quality factor can evaluate the image fusion for target recognition quantitatively and reasonably, and the evaluation results are in accordance with the visual effect of the fusion images.
Tài liệu tham khảo
citation_title=Image fusion and recognition; citation_publication_date=2008; citation_id=CR1; citation_author=W-G Liu; citation_publisher=Publishing House of the Electronics Industry
citation_title=Image fusion: algorithms and applications; citation_publication_date=2008; citation_id=CR2; citation_author=T Stathaki; citation_publisher=Academic Press
Wei, Q.: Infrared and visible image fusion methods and evaluation indexes research. Dissertation, North Minzu University (2018)
citation_journal_title=Digit Technol Appl; citation_title=Infrared and visible image fusion algorithm based on target extraction; citation_author=YD Li, JP Meng; citation_volume=36; citation_issue=03; citation_publication_date=2018; citation_pages=138-207; citation_id=CR4
Dai, L.Y., Liu, G., Xiao, G., Ruan, J.J., Zhu, J.H.: Infrared and visible image fusion based on FRC algorithm. Control Decis.1–9 (2020)
citation_journal_title=Command Inform Syst Technol; citation_title=Infrared and visible image fusion method based on deep learning; citation_author=C Xie, J Xu, X Li, W Wu; citation_volume=11; citation_issue=02; citation_publication_date=2020; citation_pages=15-20+38; citation_id=CR6
citation_journal_title=J Xianyang Normal Univ; citation_title=Infrared and visible image fusion using PCNN in NSCT domain; citation_author=F Wu, X You, Q Zhao; citation_volume=34; citation_issue=02; citation_publication_date=2019; citation_pages=67-71; citation_id=CR7
citation_journal_title=J Front Comp Sci Technol; citation_title=Review of image fusion quality evaluation methods; citation_author=Y Yang, J Li, Y Wang; citation_volume=12; citation_issue=07; citation_publication_date=2018; citation_pages=1021-1035; citation_id=CR8
Xu, Y.: Research on quality index of image fusion. Dissertation, University of Electronic Science and Technology of China (2019)
ITU- R.: BT.500-11 Methodology for the subjective assessment of the quality of television pictures (2002)
citation_journal_title=Acta Autom Sin; citation_title=Validation and correlation analysis of metrics for evaluating performance of imagefusion; citation_author=X Zhang, X Li, J Li; citation_volume=40; citation_issue=2; citation_publication_date=2014; citation_pages=306-315; citation_id=CR11
Yang, M., Cao, Y., Tan, L., et al.: A new multi-quality method in visual sensor network. In: Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Kaohsiung, China, Nov 26–28, 2007. Washington: IEEE Computer Society, 2007:667–670 (2007)
citation_journal_title=Pattern Recogn. Lett.; citation_title=Evaluation of focus measures in multi-focus image fusion; citation_author=W Huang, Z Jing; citation_volume=28; citation_issue=4; citation_publication_date=2007; citation_pages=493-500; citation_doi=10.1016/j.patrec.2006.09.005; citation_id=CR13
citation_journal_title=Infrared; citation_title=Overview of quality evaluation methods of fused infrared and visible images; citation_author=Y Wang, Z Tao; citation_volume=33; citation_issue=6; citation_publication_date=2012; citation_pages=7-11; citation_id=CR14
citation_journal_title=Chin. J. Comp.; citation_title=Synthesis performance evaluation of multi-sensor image fusion; citation_author=G He, S Chen; citation_volume=31; citation_issue=3; citation_publication_date=2008; citation_pages=486-492; citation_doi=10.3724/SP.J.1016.2008.00486; citation_id=CR15
citation_journal_title=Syst. Eng. Electron.; citation_title=Objective evaluation method for image fusion based on image quality indicator; citation_author=Y Zheng, J Song, W Zhou; citation_volume=28; citation_issue=3; citation_publication_date=2006; citation_pages=463-466; citation_id=CR16
citation_journal_title=Syst. Eng. Electron.; citation_title=Novel image fusion algorithm with novel performance evaluation method; citation_author=L Yan, B Liu, D Zhou; citation_volume=29; citation_issue=4; citation_publication_date=2007; citation_pages=509-513; citation_id=CR17
citation_journal_title=Inform Fusion; citation_title=A new metric based on extended spatial frequency and its application to DWT based fusion algorithms; citation_author=Y Zheng, EA Essock, BC Hansen; citation_volume=8; citation_issue=4; citation_publication_date=2007; citation_pages=177-192; citation_doi=10.1016/j.inffus.2005.04.003; citation_id=CR18
citation_journal_title=Inform. Fusion; citation_title=A novel similarity based quality metric for image fusion; citation_author=C Yang, JQ Zhang, XR Wang; citation_volume=9; citation_issue=5; citation_publication_date=2008; citation_pages=156-160; citation_doi=10.1016/j.inffus.2006.09.001; citation_id=CR19
citation_journal_title=Acta Electron. Sin.; citation_title=An evaluation method of image fusion based on region similarity; citation_author=X Luo, WU Xiao-jun; citation_volume=38; citation_issue=5; citation_publication_date=2010; citation_pages=1152-1155; citation_id=CR20
citation_journal_title=Electron. Lett.; citation_title=Objective image fusion performance measure; citation_author=CS Xydeas, V Petrovi; citation_volume=36; citation_issue=4; citation_publication_date=2000; citation_pages=308-309; citation_doi=10.1049/el:20000267; citation_id=CR21
citation_journal_title=Inform. Fusion; citation_title=A human perception inspired quality metric for image fusion based on regional information; citation_author=H Chen, PK Varshney; citation_volume=8; citation_issue=4; citation_publication_date=2007; citation_pages=193-207; citation_doi=10.1016/j.inffus.2005.10.001; citation_id=CR22
citation_journal_title=Image Vis. Comput.; citation_title=A new automated quality assessment algorithm for image fusion; citation_author=Y Chen, RS Blum; citation_volume=27; citation_issue=9; citation_publication_date=2009; citation_pages=1421-1432; citation_doi=10.1016/j.imavis.2007.12.002; citation_id=CR23
citation_journal_title=J. Vis. Commun. Image Represent.; citation_title=On the use of joint sparse representation for image fusion quality evaluation and analysis; citation_author=Y Hu, Q Gao, B Zhang, J Zhang; citation_volume=61; citation_publication_date=2019; citation_pages=225-235; citation_doi=10.1016/j.jvcir.2019.04.005; citation_id=CR24
citation_journal_title=Geomat. Inform. Sci. Wuhan Univ.; citation_title=Fused image quality assessment based human visual characteristics; citation_author=L Xu, Q Xiao, L He; citation_volume=44; citation_issue=04; citation_publication_date=2019; citation_pages=546-554; citation_id=CR25
citation_journal_title=Trans. Beijing Inst. Technol.; citation_title=Perceptual contrast metric for visible and infrared gray fusion images; citation_author=S Gao, X Zhang, W Jin; citation_volume=38; citation_issue=07; citation_publication_date=2018; citation_pages=715-720; citation_id=CR26
citation_journal_title=IFAC Pap Line; citation_title=Saliency difference based objective evaluation method for a superimposed screen of the HUD with various background; citation_author=HL Liu, T Hiraoka; citation_volume=52–19; citation_issue=2019; citation_publication_date=2019; citation_pages=323-328; citation_doi=10.1016/j.ifacol.2019.12.073; citation_id=CR27
citation_journal_title=ITIB; citation_title=Infrared and visible image fusion objective evaluation method; citation_author=D Ledwon, J Juszczyk; citation_volume=2019; citation_publication_date=2019; citation_pages=268-279; citation_id=CR28
citation_journal_title=Electron. Test; citation_title=Performance evaluation algorithm for infrared and visible Image fusion based on intuitionistic fuzzy; citation_author=YH Zhu, YN Zhou; citation_volume=Z1; citation_publication_date=2017; citation_pages=49-51+53; citation_id=CR29
citation_journal_title=Comp. Knowl. Technol.; citation_title=Quality evaluation method for infrared and visible images fusion based on group clustering; citation_author=YH Zhu, YN Zhou; citation_volume=13; citation_issue=09; citation_publication_date=2017; citation_pages=170-172.e174; citation_id=CR30
citation_journal_title=Syst. Eng. Electron.; citation_title=Image fusion based on region and directional variance weighted entropy; citation_author=M Guo, SM Wang; citation_volume=35; citation_issue=4; citation_publication_date=2013; citation_pages=720-725; citation_id=CR31