, PUBLICATIONS
, Wavelet Decomposition in Laplacian Pyramid for Image Fusion, International Journal of Signal Processing Systems, vol.4, issue.1, pp.37-44, 2016.
DOI : 10.12720/ijsps.4.1.37-44
URL : https://hal.archives-ouvertes.fr/hal-01316047
, Multi-focus image fusion using Laplacian Pyramid technique based on Alpha-Stable filter
URL : https://hal.archives-ouvertes.fr/hal-01939310
, Pixel level multi-focus image fusion based on local variability
, Multi-focus Image fusion using Dempster Shafer Theory based on local variability
, Pyramid method in image processing, RCA Engineer, vol, vol.29, issue.6, pp.31-41, 1984.
, A depth estimation algorithm with a single image, Optics Express, vol.15, issue.8, 2007.
DOI : 10.1364/OE.15.005024
, SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling, IEEE Transactions on Geoscience and Remote Sensing, vol.41, issue.8, pp.1773-1784, 2003.
DOI : 10.1109/TGRS.2003.813488
, The laplacian pyramid as a compact image code, IEEE Transactions on Communication, vol.31, issue.40, 1983.
, Multi-focus image fusion using multi-scale decomposition and saliency detection Ain Shams Engineering Journal, 2016.
, Near-invariant blur for depth and 2D motion via time-varying light field analysis, ACM Transactions on Graphics, vol.32, issue.2, p.13, 2013.
DOI : 10.1145/2451236.2451239
, Enhanced image capture through fusion, 1993 (4th) International Conference on Computer Vision, pp.173-182, 1993.
DOI : 10.1109/ICCV.1993.378222
, Some aspects of Dempster-Shafer evidence theory for classification of multi-modality medical images taking partial volume effect into account, Pattern Recognition Letters, vol.17, issue.8, pp.905-919, 1996.
DOI : 10.1016/0167-8655(96)00039-6
, Fusion of Image Information under imprecision and uncertainty: numerical methods. Data fusion and perception. G. Della Riccia et al, 2001.
, Information Fusion in Signal and Image Processing, 2008.
DOI : 10.1002/9780470611074
, The Pyramid as a Structure for Efficient Computation, Multiresolution Image Processing and Analysis, 1984.
DOI : 10.1007/978-3-642-51590-3_2
, Fuzzy fusion techniques for linear features detection in multitemporal SAR images, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.3, pp.122-1305, 1999.
DOI : 10.1109/36.763290
URL : https://hal.archives-ouvertes.fr/hal-00799807
, Technology for multi-focus image fusion based on wavelet transform, Advanced Computational Intelligence (IWACI), 2010.
, Extended Depth-of-Field Microscope Imaging: MPP Image Fusion VS. WAVEFRONT CODING, 2006 International Conference on Image Processing, pp.2533-2536, 2006.
DOI : 10.1109/ICIP.2006.312957
, When Does Computational Imaging Improve Performance?, IEEE Transactions on Image Processing, vol.22, issue.2, pp.447-458, 2013.
DOI : 10.1109/TIP.2012.2216538
URL : http://www1.cs.columbia.edu/CAVE/publications/pdfs/Cossairt_TIP12.pdf
, Multifocus image fusion scheme using focused region detection and multiresolution, Optics Communications, vol.284, issue.19, pp.4376-4389, 2011.
DOI : 10.1016/j.optcom.2011.05.046
, Diffusion coded photography for extended depth of field, ACM Trans. on Graphics, vol.29, issue.4, p.31, 2010.
DOI : 10.1145/1833351.1778768
, Upper and Lower Probabilities Induced by a Multivalued Mapping, The Annals of Mathematical Statistics, vol.38, issue.2, pp.325-339, 1967.
DOI : 10.1214/aoms/1177698950
, A Generalization of Bayesian Inference, Journal of the Royal Statistical Society, Series B (methodological), vol.30, pp.205-247, 1968.
DOI : 10.1007/978-3-540-44792-4_4
, Reasoning with imprecise belief structures, International Journal of Approximate Reasoning, vol.20, issue.1, pp.79-111, 1999.
DOI : 10.1016/S0888-613X(00)88944-6
, An Image Fusion Algorithm Based on Discrete Wavelet Transform and Canny Operator Advance Research on Computer Education , Simulation and Modelling Communication in, Computer and Information Science, vol.175, pp.32-38, 2011.
, Local Scale Control for Edge Detection and Blur Estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.7, 1998.
DOI : 10.1007/3-540-61123-1_127
URL : http://www.cs.ualberta.ca/~nray1/CMPUT605/track3_papers/EZ.pdf
, Steerable local frequency based multispectral multifocus image fusion, Information Fusion, vol.23, pp.99-115, 2015.
DOI : 10.1016/j.inffus.2014.07.003
, Medical image fusion by wavelet transform modulus maxima, Optics Express, vol.9, issue.4, pp.184-190, 2001.
DOI : 10.1364/OE.9.000184
, Image Fusion, Information fusion, vol.8, pp.114-118, 2007.
DOI : 10.1002/0471724270.ch8
, Survey on multi-focus image fusion algorithms, 2014 Recent Advances in Engineering and Computational Sciences (RAECS), 2014.
DOI : 10.1109/RAECS.2014.6799615
, Digital Image Processing, 2002.
, Infinite-variance, alpha-stable shocks in monetary SVAR, International Review of Applied Economics, vol.39, issue.5, pp.755-786, 2012.
DOI : 10.1017/S0266466608080286
, Object recognition based on Dempster-Shafer reasoning Intelligent Robots and Computer vision VII Real-time fusion of multifocus images for visual sensor networks, Proc. SPIE 1002 Machine vision and image processing, 1989.
, Pyramid based texture analysis/Syntesis, Proc. 22nd Annual Conference on Computer Graphics and Interactive Techniques, pp.229-238, 1995.
, Enhanced image fusion algorithm using laplacian pyramid and spatial frequency based wavelet algorithm, International Journal of Soft Computing and Engineering, vol.1, issue.5, 2011.
, Investigation of image fusion for remote sensing application, 2013.
, Fuzzy sets, uncertainty and information. Englewood Cliffs, 1988.
, Survey on multifocus image fusion techniques, 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), pp.1420-1425, 2016.
DOI : 10.1109/ICEEOT.2016.7754918
, Analysis of Image Fusion Techniques based on Quality Assessment Metrics, Indian Journal of Science and Technology, vol.9, issue.31, pp.1-8, 2016.
DOI : 10.17485/ijst/2016/v9i31/92553
URL : http://www.indjst.org/index.php/indjst/article/download/92553/72523
, Tchebichef moment based restoration of Gaussian blurred images, Applied Optics, vol.55, issue.32, pp.9006-9016, 2016.
DOI : 10.1364/AO.55.009006
, A Survey on pattern classification with missing data using Dempster Shafer theory, International Conference on Information Engineering, pp.134-138, 2015.
, Image partial blur detection and classification. Computer Vision and Pattern Recognition, 2008.
, Multisensor Image Fusion Using the Wavelet Transform, Graphical Models and Image Processing, vol.57, issue.3, pp.235-245, 1995.
DOI : 10.1006/gmip.1995.1022
, Multifocus image fusion scheme based on feature contrast in the lifting stationary wavelet domain, EURASIP Journal on Advances in Signal Processing, vol.38, issue.7, 2012.
DOI : 10.1109/72.761706
URL : https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/1687-6180-2012-39?site=asp-eurasipjournals.springeropen.com
, Multimodality image registration by maximization of mutual information, IEEE Transactions on Medical Imaging, vol.16, issue.2, 1997.
DOI : 10.1109/42.563664
URL : https://lirias.kuleuven.be/bitstream/123456789/28116/1/Maes97TMI.pdf
, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.7, pp.674-683, 1989.
DOI : 10.1109/34.192463
URL : https://repository.upenn.edu/cgi/viewcontent.cgi?article=1703&context=cis_reports
, Particle filtering with alpha-stable distributions, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005, pp.381-386, 2005.
DOI : 10.1109/SSP.2005.1628625
URL : http://www.lancs.ac.uk/~mihaylov/IEEE_SSP_05_A235.pdf
, Color Image Segmentation Using The Dempster- Shafer Theory of Evidence for The Fusion of Texture, Proceeding ISPRS Volume XXXIV-3/W8, pp.139-144, 2003.
, Extended Depth-of-Field 3-D Display and Visualization by Combination of Amplitude-Modulated Microlenses and Deconvolution Tools, Journal of Display Technology, vol.1, issue.2, pp.321-327, 2005.
DOI : 10.1109/JDT.2005.858883
, Challenges and opportunities of multimodality and data fusion in remote sensing, Proceeding of the IEEE, vol.103, issue.9, pp.1585-1601, 2015.
, Shape from focus system, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.302-308, 1992.
DOI : 10.1109/CVPR.1992.223259
, Multiresolution-based image fusion with additive wavelet decomposition, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.3, pp.1204-1211, 1999.
DOI : 10.1109/36.763274
URL : http://diposit.ub.edu/dspace/bitstream/2445/8545/1/500850.pdf
, Pixel-level Image Fusion using Wavelets and Principal Component Analysis, Defence Science Journal, vol.58, issue.3, pp.338-352, 2008.
DOI : 10.14429/dsj.58.1653
URL : http://publications.drdo.gov.in/ojs/index.php/dsj/article/download/1653/747
, Signal processing with Alpha-Stable distributions and applications (Adaptive and Learning Systems for Signal Processing, Communications and Control Series), 1995.
, The Fourier transform and its applications, 2009.
, Stathaki Image Fusion: An Overview, Fifth International Conference on Intelligent Systems, Modelling and Simulation, 2014.
DOI : 10.1109/isms.2014.58
, A wavelet-based image fusion tutorial, Pattern Recognition, vol.37, 2004.
, A new sense for depth of field, IEEE Transactions on Pattern Analysis and Machine Intelligent, vol.9, issue.4, pp.523-531, 1987.
, An Overview of Different Image Fusion Methods for Medical Applications, International Journal of Scientific & Engineering Research, vol.4, issue.7, pp.129-133, 2013.
, Wavelet based texture modeling for the classification of very high resolution maritime pine forest images, 2014 IEEE Geoscience and Remote Sensing Symposium, 2014.
DOI : 10.1109/IGARSS.2014.6946861
URL : https://hal.archives-ouvertes.fr/hal-01064405
, Wavelet-Based Texture Features for the Classification of Age Classes in a Maritime Pine Forest, IEEE Geoscience and Remote Sensing Letters, 2015.
DOI : 10.1109/LGRS.2014.2353656
URL : https://hal.archives-ouvertes.fr/hal-01716751
, Study of Dempster???Shafer theory for image segmentation applications, 61] K. Sentz and S. Ferson. Combination of Evidence in Dempster-Shafer Theory. SAND2002-0835 Technical Report. Sandia National Laboratories, pp.15-23, 2002.
DOI : 10.1016/S0262-8856(01)00070-1
, A mathematical theory of evidence, 1976.
, Multifocus and multispectral image fusion based on pixel significance using multiresolution decomposition, Signal Image and Video Processing, pp.95-109, 2013.
DOI : 10.1016/S0141-9382(02)00069-0
, Multi-focus image fusion using a bilateral gradient-based sharpness criterion, Optics Communications, vol.284, issue.1, pp.80-87, 2011.
DOI : 10.1016/j.optcom.2010.08.085
, Medical Image Fusion via an Effective Wavelet-Based Approach, EURASIP Journal on Advances in Signal Processing, vol.27, issue.16, 2010.
DOI : 10.1016/j.patrec.2006.05.004
URL : https://doi.org/10.1155/2010/579341
, Hybrid Image Fusion Algorithm Using Laplacian Pyramid and PCA Method, Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies, ICTCS '16, 2016.
DOI : 10.1109/TIP.2004.823821
, Alignment by maximization of mutual information, Journal International of Computer Vision, vol.24, issue.2, 1997.
DOI : 10.21236/ada299525
URL : http://dspace.mit.edu/bitstream/1721.1/9918/2/40073866-MIT.pdf
, Image quality assesment: from error measurement to structural similarity, IEEE Transactions on Image Processing, vol.13, issue.1, 2004.
DOI : 10.1109/tip.2003.819861
URL : http://www.cns.nyu.edu/~zwang/files/papers/ssim.pdf
, Statistical reasoning with imprecise probabilities, 1991.
DOI : 10.1007/978-1-4899-3472-7
, A Multi-focus Image Fusion Method Based on Laplacian Pyramid, Journal of Computers, vol.6, issue.12, 2011.
DOI : 10.4304/jcp.6.12.2559-2566
, A statistical multi-scale image segmentation via Alpha-Stable modeling, IEEE International Conference on Image Processing, pp.357-360, 2007.
DOI : 10.1109/icip.2007.4380028
URL : https://research-information.bristol.ac.uk/files/3014908/Wan_IEEE_ICIP_2007.pdf
, Compressive image fusion, IEEE International Conference on Image Processing, pp.1308-1311, 2008.
, Ship Detection in SAR Image Based on the Alpha-stable Distribution, Sensors, vol.6, issue.1, pp.4948-4960, 2008.
DOI : 10.1080/15326349708807450
URL : http://www.mdpi.com/1424-8220/8/8/4948/pdf
, Sensor fusion using Dempster-Shafer theory, pp.21-23, 2002.
, Remote sensing application principles and methods, pp.253-254, 2003.
, Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm, Measurement Science Review, vol.14, issue.2, 2014.
DOI : 10.2478/msr-2014-0014
, Classic Works of the Dempster-Shafer Theory of Belief Functions, pp.1-34, 2007.
DOI : 10.1007/978-3-540-44792-4
, Medical Image Fusion via an Effective Wavelet-Based Approach, EURASIP Journal on Advances in Signal Processing, vol.27, issue.16, 2010.
DOI : 10.1016/j.patrec.2006.05.004
URL : https://doi.org/10.1155/2010/579341
, Wavelet decomposition applied to image fusion, Proc. Int. Conf. on Info-tech and Info-net, pp.291-295, 2001.
, Low Level Fusion of Imagery Based on Dempster-Shafer Theory, Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, pp.475-479, 2003.
, Data fusion for pattern classification via the Dempster-Shafer evidence theory, Proc. IEEE Int. Conf. Syst, pp.109-114, 2002.
, Stochastic resonance in a simple threshold sensor system with Alpha Stable noise The Smithsonian, Communications in Theoretical PhysicsNASA Astrophysics Data System, vol.61, pp.578-582, 2014.
DOI : 10.1088/0253-6102/61/5/06
, Medical image fusion algorithm on the Laplace- PCA. Proc. 2013 Chinese Intelligent Automation Conference, pp.787-794, 2013.
, Multi-focus image fusion based on the neighbor distance, Pattern Recognition, vol.46, issue.3, pp.1002-1011, 2013.
DOI : 10.1016/j.patcog.2012.09.012
, A novel explisit multi-focus image fusion method, Journal of Information Hiding and Multimedia Signal Processing, pp.600-612, 2015.
, Multi-focus image fusion algorithm based on compound PCNN in Surfacelet domain, Optik - International Journal for Light and Electron Optics, vol.125, issue.1, pp.296-300, 2014.
DOI : 10.1016/j.ijleo.2013.07.002
, Remote sensing application principles and methods, LIST OF FIGURES, pp.253-254, 2003.
,
,
,
, , p.13
, Schematic diagram for the multi-focus image fusion using energy of Laplacian and guided filter, p.17
, , p.30
, , p.32
, , p.36
, Source images 'clock': (a) image with focus on the small clock, (b) image with focus on the big clock, p.37
, LP(maximum), DWT, and proposed method, RMSE of the LP(average), p.38
, LP(maximum), DWT, and proposed method, PSNR of the LP(average), p.38
, LP(maximum), DWT, and proposed method, Average, p.39
, Multi-focus images:(I 1 ) in focus on the small bottle, (I 2 ) in focus on the gear and (I 3 ) in focus on the big bottle, p.40
, The results of combination fusion, p.41
, Pixel at (x, y) within its neighborhood, p.46
, , p.49
, Comparison of visual quality of fused images various methods for image, p.50
, Comparison of visual quality of fused images various methods for image, p.51
, Two multi focus images, the yellow part is blurred area. And the white part is clear(focused) area, p.54
, , p.58
, , p.59
, , p.59
, The images used in the experiment, p.61
, Experiment results of multi-focus image fusion image 'bird, p.62
, Experimental results of multi-focus image fusion image 'bottle, p.64
, Experimental results of multi-focus image fusion image 'building
, Comparison of different multi-focus image fusion methods
, Performance evaluation of the fused image 'bottle, p.39
, Performance evaluation of the fused image 'bottle, p.41
, Performance evaluation measures of fused images, p.52
, , p.63
, Performance evaluation image 'bottle, p.65
, Performance evaluation image 'building, p.66
, Table RMSE of 150 images for LP(DWT) method, p.88
, Table RMSE of 150 images for DST method and NLV method, p.91
, 7628 13.8193 2.1084 27 0.7223 4.9991 0.5954 3.3709 2.5427 1.9039 18.1974 19.9892 3.3580 28 1.1951 4.2662 0.5561 2.0033 1.0189 3.0640 10.2646 13.6351 3.3378 29 0.4330 3.5392 0.4321 1.4915 0.7810 2.2477 8.6253 12.9653 1.7949 30 2.3955 3.5651 0.7521 1.9504 1.2940 3, 1984.
, .7531 2.0868 1.3213 2.1937 11.5892 15.1582 2.6999 76 0.7359 5.9656 0.4109 2.0094 0.5254 6.3150 9.7482 9.8887 3.4813 77 0.3776 3.6548 0.4416 1.4770 0.5028 3.8559 4
, Table RMSE of 150 images for DST method and NLV method B SOFTWARE IMPLEMENTATION B.1/ BLURRING IMAGE 1 function [ im1,im2 ] = blur image( imr,s,v ) 2 %input image: imr (reference image), v (variance of Gaussian filter, pp.3-5
, 6 [rows, columns] = size(imr)
,
, 9 rightHalf = imr(:, midColumn+1:end)
, 10 11 [x,y]=meshgrid(-s:1:s)
, 13 r=((x)?2+(y).?2).?(0.5)
, 17 tg=t/sum(sum(t))
, 19 blurryLeft = imfilter(leftHalf, tg
, 20 blurryRight = imfilter(rightHalf, tg
, 21
, D1, vol.24, pp.1-2
, 25 figure,imshow(im1),title('blurry right
, G1, vol.28, pp.2-2
, 29 figure,imshow(im2),title('blurry left, p.30
, 31 end B.2/ LAPLACIAN PYRAMID IMAGE FUSION B.2, p.93
, 18 for I=2:(C-1)
, 19 g1(I,1)=sum(sum(wtemp. * g0(2 * I-3:2 * I+1
, 23 for I=2:(C-1)
, =sum(sum(wtemp. * g0(2 * I-3:2 * I+1, pp.24-25
, 28 for I=2:(R-1)
, 29 g1(1,I)=sum(sum(wtemp. * g0(1:3,2 * I-3:2 * I+1)))
, 33 for I=2:(R-1)
, C+1)/2,I)=sum(sum(wtemp. * g0(C-2:C,2 * I-3:2 * I+1))), p.1
, 37 %compute 4 corners of the output image 38 wtemp=w
, 1)=sum(sum(wtemp, pp.41-42
, R+1)/2)=sum(sum(wtemp. * g0, pp.43-44
, R+1)/2)=sum(sum(wtemp. * g0(C-2:C,R-2:R))), pp.45-46
, EXPAND FUNCTION 1 function[gl1]=expand(gl0, p.=size
, C-1,1:R-1) * w(4,4)+gl0(2:C,1:R-1) *, :R) * w(4,2)+gl0(2:C,2:R) * w, p.1
, R-1) * w(5,4)+gl0(2:C-1,1:R-1) * w(3,4)+ 10 gl0(3:C,1:R-1) * w(1,4)+gl0, pp.9-10
, R-2) * w(4,5)+gl0(1:C-1,2:R-1) * w(4,3)+ 13 gl0, ) * w(2,5)+gl0(2:C,2:R-1) * w:R) * w, pp.12-13
, C-1,1:R-2) * w(3,5)+ 16 gl0(3:C,1:R-2) * w(1,5), C, vol.31155212532122135133133, issue.0211, pp.15-16
, 1)=(gl0(1:C-2,1) * w(5,3)+gl0(1:C-2,2) * w(5,1)+gl0(2:C-1,1) * w(3,3)+ 22 gl0(2:C-1,2) * w, pp.21-22
, ) * w, pp.25-26
, C-1,1) * w(4,3)+gl0(1:C-1,2) * w(4,1)+ 30 gl0, :C,1) * w(2,3)+gl0(2:C,2) * w, pp.29-30
, C-1,R) * w(4,3)+gl0(1:C-1,R-1) * w(4,5)+ 34 gl0, pp.33-34
, SOFTWARE IMPLEMENTATION 36 temp=w(3,5)+w(1,5)+w(3,3)+w(1,3)+w(3,1)+w(1,1)
, ) * w(3,3)+ 38 gl0, pp.37-38
, R-2) * w(3,5)+gl0(C-1,1:R-2) * w(5,5)+gl0(C,2:R-1) * w(3,3)+ 42 gl0(C-1, pp.41-42
, R-1) * w(3,4)+gl0(2,1:R-1) * w(1,4)+gl0, pp.45-46
, R-1) * w(3,4)+gl0(C-1,1:R-1) * w(5,4)+gl0(C, pp.48-49
, 50 %compute corners 51 temp=w(3,3)+w(3,1)+w(1,3)+w(1,1)
, ,1)=(gl0(C,1) * w(3,3)+gl0(C-1,1) * w(5,3)+gl0(C,2) * w, pp.55-56
, 57 temp=w(3,3)+w(3,5)+w(1,3)+w(1,5)
, ) * w(3,5)+gl0, pp.58-59
, 3)+gl0(C-1,R) * w(5,3)+gl0(C,R-1) * w, pp.61-62
, 3/ LP(DWT) 1 function [ f ] = fusion laplacianwavelet( im1,im2 ) 2 %image fusion using Laplacian wavelet 3 g=double(im1)
, 4 imagesize1=size(g)
, ),1) h]; %resize the image 13 h=double(h), pp.12-13
, 17 h1=reduce(h,t)
, 19 g2=reduce(g1,t)
, 21
, 22 g3=reduce(g2,t)
, 25 g4=reduce(g3,t)
, 26 h4=reduce(h3,t)
, 31 g21=expand1(g2,t)
, 34 g31=expand(g3,t)
, 37 g41=expand(g4,t)
, Lg1=g1-g21, pp.1-1
, Lg2=g2-g31, pp.2-2
, Lg3=g3-g41, pp.3-3
, 1 function d1=local variability (im1,a) 2 %input: im1 (image), a (size of neighborhood) 3 %output, p.1
, image1=double(im1)
, S=size(image1)
, i,j)-image1(i-a:i+a,j-a:j+a)?2-1), ?2)))./ ((2 * a+1, pp.10-11
, k,j)-image1(1:a+k,j-a:j+a), 11 end 12 end 13 14 for k=1:a 15 for j=a+1:S?2)))/((a+k) * (2 * a+1)-1)), pp.16-17
, S(1)-k+1,j)-image1(S(1)-k+1-a:S(1),j-a:j+a)).?2)))/((a+k) * (2 * a+1)-1)) ; 18 end 19, ?2)))/((k+a) * 2 * a-1)), pp.17-18
, ?2)))/((k+a) * 2 * a-1)), pp.25-26
, 27 end 28 29 for k=1:a 30 for j=S?2)))/((k+a) * (S(2)-j+a+1)-1)), pp.31-32
, ?2)))/ ( (a+1), pp.35-36
, ?2)))/ ((a+1), pp.36-37
, ?2)))/ ( (a+1)?2-1)), pp.37-38
, SOFTWARE IMPLEMENTATION 39 for l=1:a 40 for i=a+1:S(1)-a 41 d1(i,S(2)-l+1)=sqrt( (sum(sum((image1(i,S(2)-l+1)-image1(i-a:i+a, ?2)))/ ( (2 * a+1) * (l+a)-1))
, (i,l)-image1(i-a:i+a, ?2)))/ ((2 * a+1) * (a+l)-1 )), pp.42-43
, 43 end 44 end
, ?2)))/((k+a) *, pp.47-48
, 51 for k=S(1)-a+1:S(1), p.52
, ?2)))/((S(1)-k+a+1) * (S(2)-j+a+1)-1)), pp.53-54
, 54 end 55 end 56 57 for k=1:a 58 for i=S(1)-a+1:S?2)))/((S(1)-i+a+1) * (k+a)-1)), pp.59-60
, MULTI-FOCUS IMAGE FUSION USING DST BASED ON LOCAL VARIABILITY 1 function [f dst ] = fusion dst( image1, image2,a ) 2 %UNTITLED4 Summary of this function goes here 3 % Detailed explanation goes here
, image1=double(image1)
, S=size(image1)
, 13 %d=abs(d1-d2)
, 18 mean md1=mean(mean(md1))
, ?2))/(S(1) * S, pp.1-1
, 20 m1ac1=md1. * (1-std md1)
, 28 mean md2=mean(mean(md2))
, ?2))/(S(1) * S, pp.2-2
, 30 m1bc1=md2. * (1-std md2)
, 31 m1bc3=std md2 * ones([S(1) S
, 32 m1bc2=1-m1bc1-m1bc3
, 34 pls1=m1ac1+m1ac3; 35 pls2=m1bc1+m1bc3, 37 for i=1:S(1) 38 for j=1:S, p.39
, if pls1(i,j)<pls2(i,j)
, dst(i,j)=image1(i,j)
, 41 elseif pls1(i,j)>pls2(i,j)
, dst(i,j)=image2(i,j)
, 43 elseif pls1(i,j)==pls2(i,j)
, j)+image2(i,j))/2; 45 end 46 end 47 end 48 end 1 function, p.2
, imf=fusion dst(im1,im2,a)
, y=RMSE; 1 for a=1:10 (a)=rmse dst(imr,im1, p.2
, %final fused image of DST-LV: F 8 F=fusion dst(imr,im1,im2
, MULTI-FOCUS IMAGE FUSION USING NLV 1 %Model of size of neighborhood (a) 2 function [a] = size neighborhood( v,s ) 3 %v = variance of blurring filter, s = size of blurring filter 4 a=(3.0384761/(1+29.0909139 * exp(-0.5324955 * s))) * log(v), * ((log(s)-2.655551)/-1.22175)?2)
, 9 %Multi-focus image fusion using NLV 10 function [ f ] = fusion NLV( im1,im2,a ) 11 %image fusion using neighborhood local variability 12, p.1
, 13 im2=double(im2)
, S=size(im1)
, 20 for j=1:S(2) 21 f(i,j)=(exp(d1(i,j)). * im1(i,j)+exp(d2(i,j)). * im2(i,j)), pp.22-23
, 23 end 24 end 25 end Document generated with L AT E X and: the L AT E X style for PhD Thesis created by S. Galland ? http://www.multiagent.fr/ThesisStyle the tex-upmethodology package suite ? http