Abstract:An image can be decomposed into texture part and cartoon part adhering to different geometric features. An image fusion method based on these two features is proposed in this paper. A cartoon dictionary and a texture dictionary are learned from the sample images based on their different cartoon and texture features. In the fusion process, the cartoon and texture parts of the source image are fused using the specific cartoon and texture dictionary respectively. Experimental results show that the proposed method is very effective.
[1] LIU Z, FORSYTH D S, SAFIZADEH M S,et al. A data-fusion scheme for quantitative image analysis by using locally weighted regression and Dempster-Shafer theory[J]. IEEE Transactions on Instrumentation and Measurement,2008,57(11):2554-2560.
[2] HASSAINIA F, MAGAFIA I, LANGEVIN F. Image fusion by an orthogonal wavelet transform and comparison with other methods[C]//International Conference of the IEEE Engineering in Medicine and Biology Society. Paris:The IEEE Engineering in Medicine and Biology Society, 1992(3):1246-1247.
[3] PETROVIC V S, XYDEAS C S. Gradient-based multiresolution image fusion[J]. IEEE Transactions on Image Processing, 2004, 13(2):228-237.
[4] LI H, MANJUNATH B, MITRA S. Multisensor image fusion using the wavelet transform[J].Graphical Models and Image Processing, 1995, 57(3):235-245.
[5] HILL P, CANAGARAJAH N C, BULL D R. Image fusion using complex wavelet[C]//Proc of the 13th British Machine Vision Conference. Durham:British Machine Vision Association, 2002:487-496.
[6] 常莉红. 一种基于四元数小波变换的图像融合方法[J]. 宝鸡文理学院学报(自然科学版), 2016, 36(3):8-14. CHANG L H. An image fusion method based on quaternion wavelet transform[J].Journal of Baoji University of Art and Sciences(Natural Science Edition), 2016, 36(3):8-14.
[7] YANG B, LI S T. Multifocus image fusion and restoration with sparse representation[J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(4):884-892.
[8] LIU Y,WANG Z F. Simultaneous image fusion and denoising with adaptive sparse representation[J]. IET Image Processing, 2014, 9(5):347-357.
[9] LIU Y, LIU S P, WANG Z F. A general framework for image fusion based on multi-scale transform and sparse representation[J].Information Fusion, 2015, 24:147-164.
[10] YIN H T, LI S T, FANG L Y. Simultaneous image fusion and super-resolution using sparse representation[J]. Information Fusion, 2013, 14(3):229-240.
[11] BUADES A, LE T, MOREL J, et al. Cartoon +Texture image decomposition[J].Image Processing on Line, 2011(1):200-207.
[12] AHARON M, ELAD M, BRUCKSTEIN A. K-SVD:An algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006, 54(11):4311-4322.
[13] HOSSNY M, NAHAVANDI S, CREIGHTON D. Comments on ‘Information measure for performance of image fusion’[J]. Electronics Letters,2008, 44(18):1066-1067.
[14] XYDEAS C S, PETROVIÉ V. Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4):308-309.
[15] LIU Z, BLASCH E, XUE Z Y,et al. Objective assessment of multiresolution image fusion algorithms for context enhancement in night vision:A comparative study[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012,34(1):94-109.