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An Overview of Multiresolution Analysis for Nondestructive Evaluation of Pavement Surface Drainage

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Abstract

Network level drainage assessment of the pavement surface plays a crucial role in controlling and decreasing the accident rate. Hydroplaning is one of the major causes of accidents in wet weather conditions and is the consequence of low drainage quality of pavement surfaces. Since no automated system currently exists for the pavement drainage evaluation, this work was conducted to present a new system to assess drainage process quality. For this aim, the saturation situation was simulated for pavement surface and photo acquisition was carried out on the drainage process of pavement surface after saturation. Finally, image processing method was applied to produce an index related to drainage quality. Using a proper method to enhance and prepare these images for the analysis step and find appreciate feature for the drainage quality is also among the necessities of drainage assessment. After a brief overview of multiresolution analysis, we revise the state-of-the-art of multiresolution analysis methods by discussing assessing parameters for asphalt surface image enhancement in nondestructive evaluation, formulated and fused to allow for a general comparison. In this work, different transform methods are used for asphalt surface image enhancement and a comparison is made between wavelet, curvelet, ridgelet, shearlet, and contourlet transforms by assessing parameters including TIME, PSNR, SNR, MSE, MAE, MSE, UQI, and SSIM. The comparison among the obtained results shows the superiority of shearlet transform over other transforms in providing of processed images with higher quality. Furthermore, it was found that ridgelet transform is more suitable for the jobs which time is the main parameter.

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References

  1. Bhutada G, Anand R, Saxena S (2011) Edge preserved image enhancement using adaptive fusion of images denoised by wavelet and curvelet transform. Digital Signal Process 21(1):118–130

    ArticleΒ  Google ScholarΒ 

  2. Jaiswal A, Upadhyay J, Somkuwar A (2014) Image denoising and quality measurements by using filtering and wavelet based techniques. AEU-Int J Electron Commun 68(8):699–705

    ArticleΒ  Google ScholarΒ 

  3. Maini R, Aggarwal H (2010) A comprehensive review of image enhancement techniques. arXiv preprint arXiv 1003:4053

    Google ScholarΒ 

  4. Hedaoo P, Godbole SS (2011) Wavelet thresholding approach for image denoising. Int J Netw Secur Appl (IJNSA) 3(4):16–21

    Google ScholarΒ 

  5. Rosenfeld A, Kak AC (2014) Digital picture processing. vol.Β 1. Elsevier, Amsterdam

    MATHΒ  Google ScholarΒ 

  6. Jain AK (1989) Fundamentals of digital image processing. Prentice-Hall, Inc, New Delhi

    MATHΒ  Google ScholarΒ 

  7. Ji T-L, Sundareshan MK, Roehrig H (1994) Adaptive image contrast enhancement based on human visual properties. IEEE Trans Med Imaging 13(4):573–586

    ArticleΒ  Google ScholarΒ 

  8. Agaian S (1990) Advances and problems of the fast orthogonal transforms for signal-images processing applications (part 1). Pattern recognition, classification, forecasting. Yearbook, The Russian Academy of Sciences, Nauka, Moscow, ppΒ 146–215

    Google ScholarΒ 

  9. Agaian S (1991) Advances and problems of fast orthogonal transform for signal/image processing applications. Part 1:146–215

  10. Aghagolzadeh S, Ersoy OK (1992) Transform image enhancement. Opt Eng 31(3):614–626

    ArticleΒ  Google ScholarΒ 

  11. Wang DC, Vagnuccin AH, Li C (1983) Digital image enhancement: a survey. Comput Vis Gr Image Process 24(3):363–381

    ArticleΒ  Google ScholarΒ 

  12. Morrow WM et al (1992) Region-based contrast enhancement of mammograms. IEEE Trans Med Imaging 11(3):392–406

    ArticleΒ  Google ScholarΒ 

  13. Beghdadi A, Le Negrate A (1989) Contrast enhancement technique based on local detection of edges. Comput Vis Gr Image Process 46(2):162–174

    ArticleΒ  Google ScholarΒ 

  14. Gonzalez RC, Woods RE (2002) Digital image processing. Prentice hall, Upper Saddle River

    Google ScholarΒ 

  15. Grigoryan AM, Agaian SS (2004) Transform-based image enhancement algorithms with performance measure. Adv Imaging Electron Phys 130:165–242

    ArticleΒ  Google ScholarΒ 

  16. Agaian SS, Panetta K, Grigoryan AM (2001) Transform-based image enhancement algorithms with performance measure. IEEE Trans Image Process 10(3):367–382

    ArticleΒ  MATHΒ  Google ScholarΒ 

  17. Starck, J-L, Elad M, Donoho D (2004) Redundant multiscale transforms and their application for morphological component separation. Adv Imaging Electron Phys. 132(82):287–348

    ArticleΒ  Google ScholarΒ 

  18. Li J (2003) A wavelet approach to edge detection. Sam Houston State University, Huntsville

    Google ScholarΒ 

  19. Daubechies I (1988) Orthonormal bases of compactly supported wavelets. Commun Pure Appl Math 41(7):909–996

    ArticleΒ  MathSciNetΒ  MATHΒ  Google ScholarΒ 

  20. Mallat SG (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans Pattern Anal Mach Intell 11(7):674–693

    ArticleΒ  MATHΒ  Google ScholarΒ 

  21. Mallat SG, Zhong S (1989) Complete signal representation with multiscale edges. New York University, Courant Institute of Mathematical Sciences, Computer Science Division, New York

    Google ScholarΒ 

  22. Piao Y, Shin L-H, Park H (2007) Image resolution enhancement using inter-subband correlation in wavelet domain. In: Image Processing, 2007. IEEE International Conference on ICIP 2007.

  23. Demirel H, Anbarjafari G (2010) Satellite image resolution enhancement using complex wavelet transform. IEEE Geosci Remote Sens Lett 7(1):123–126

    ArticleΒ  Google ScholarΒ 

  24. Atkins CB, Bouman CA, Allebach JP (2001) Optimal image scaling using pixel classification. in Image Processing, 2001. Proceedings. 2001 International Conference on. 2001. IEEE.

  25. Carey WK, Chuang DB, Hemami SS (1999) Regularity-preserving image interpolation. IEEE Trans Image Process 8(9):1293–1297

    ArticleΒ  Google ScholarΒ 

  26. Mallat S (1999) A wavelet tour of signal processing, (Wavelet analysis & its applications)

  27. Candes EJ (1998) Ridgelets: theory and applications, Stanford University, Stanford

    Google ScholarΒ 

  28. CandΓ¨s EJ, Donoho DL (1999) Ridgelets: a key to higher-dimensional intermittency? Philos Trans R Soc Lond A 357(1760):2495–2509

    ArticleΒ  MathSciNetΒ  MATHΒ  Google ScholarΒ 

  29. Deans SR (2007) The Radon transform and some of its applications. Courier Corporation, North Chelmsford

    MATHΒ  Google ScholarΒ 

  30. Bolker ED (1987) The finite Radon transform. Contemp Math 63:27–50

    ArticleΒ  MathSciNetΒ  MATHΒ  Google ScholarΒ 

  31. Campisi P, Neri A, Scarano G (2002) Model based rotation-invariant texture classification. In: Proceedings. 2002 International Conference on Image Processing (IEEE).

  32. Candes EJ, Donoho DL (2000) Curvelets: a surprisingly effective nonadaptive representation for objects with edges. DTIC Document

  33. Guo K et al (2006) Wavelets with composite dilations and their MRA properties. Applied and Computational Harmonic. Analysis 20(2):202–236

    MathSciNetΒ  MATHΒ  Google ScholarΒ 

  34. Labate D et al (2005) Sparse multidimensional representation using shearlets. In Optics & Photonics 2005. International Society for Optics and Photonics.

  35. Guo K, Labate D (2007) Optimally sparse multidimensional representation using shearlets. SIAM J Math Anal 39(1):298–318

    ArticleΒ  MathSciNetΒ  MATHΒ  Google ScholarΒ 

  36. Do M, Vetterli M (2003) Contourlets. In: Stoeckler J, Welland GV, (eds) Beyond wavelet, Academic Press, New York

    Google ScholarΒ 

  37. Do M, Vetterli M (2003) Contourlet: A computational framework for directional multiresolution image representation. In IEEE Trans. Image Proc.

  38. Do MN (2001) D.M.I., Representations [Ph. D. dissertation]. Swiss Federal Institute of Technology

  39. Eslami R, Radha H.(2003) On low bit-rate coding using the contourlet transform. In Signals, Systems and Computers, 2004. Conference record of the thirty-seventh Asilomar Conference on. 2003. IEEE.

  40. Gonzalez R, Woods R (2008) Digital image processing. Pearson prentice hall, Upper Saddle River

    Google ScholarΒ 

  41. Pratt WK (2009) Digital image processing. 3rd edn. Wiley, New York

Download references

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Correspondence to H. Zakeri.

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Appendix A: Filter Coefficients

Appendix A: Filter Coefficients

Let \(h\) and \(g\) be the wavelet decomposition (analysis) filters, where \(h~\)is a lowpass filter and \(g\) is a highpass filter. Let the dual filters \({h'}~\)and \(g'\) be the wavelet reconstruction (synthesis) filters. The coefficients of the wavelet filters are shown in the following sections:

Note:Wavelets are indexed by the number of vanishing moments; for example, β€œdaubechies 2” has two vanishing moments and four tap filters.

Haar

h0 = 0.7071067812

g0 =β€‰βˆ’0.7071067812

hβ€² 0 = 0.7071067812

gβ€² 0 = 0.7071067812

h1 = 0.7071067812

g1 = 0.7071067812

hβ€² 1 = 0.7071067812

gβ€² 1 =β€‰βˆ’0.7071067812

Daubechies

β€˜db1’

h0 = 0.7071067812

g0 =β€‰βˆ’0.7071067812

hβ€² 0 = 0.7071067812

gβ€² 0 = 0.7071067812

h1 = 0.7071067812

g1 = 0.7071067812

hβ€² 1 = 0.7071067812

gβ€² 1 =β€‰βˆ’0.7071067812

β€˜db2’

h0 =β€‰βˆ’0.1294095226

g0 =β€‰βˆ’0.4829629131

hβ€² 0 = 0.4829629131

gβ€² 0 =β€‰βˆ’0.1294095226

h1 = 0.2241438680

g1 = 0.8365163037

hβ€² 1 = 0.8365163037

gβ€² 1 =β€‰βˆ’0.2241438680

h2 = 0.8365163037

g2 =β€‰βˆ’0.2241438680

hβ€² 2 = 0.2241438680

gβ€² 2 = 0.8365163037

h3 = 0.4829629131

g3 =β€‰βˆ’0.1294095226

hβ€² 3 =β€‰βˆ’0.1294095226

gβ€² 3 =β€‰βˆ’0.4829629131

β€˜db10’

h0 =β€‰βˆ’0.0000132642

g0 =β€‰βˆ’0.0266700579

hβ€² 0 = 0.0266700579

gβ€² 0 =β€‰βˆ’0.0000132642

h1 = 0.0000935887

g1 = 0.1881768001

hβ€² 1 = 0.1881768001

gβ€² 1 =β€‰βˆ’0.0000935887

h2 =β€‰βˆ’0.0001164669

g2 =β€‰βˆ’0.5272011889

hβ€² 2 = 0.5272011889

gβ€² 2 =β€‰βˆ’0.0001164669

h3 =β€‰βˆ’0.0006858567

g3 = 0.6884590395

hβ€² 3 = 0.6884590395

gβ€² 3 = 0.0006858567

h4 = 0.0019924053

g4 =β€‰βˆ’0.2811723437

hβ€² 4 = 0.2811723437

gβ€² 4 = 0.0019924053

h5 = 0.0013953517

g5 =β€‰βˆ’0.2498464243

hβ€² 5 =β€‰βˆ’0.2498464243

gβ€² 5 =β€‰βˆ’0.0013953517

h6 =β€‰βˆ’0.0107331755

g6 = 0.1959462744

hβ€² 6 =β€‰βˆ’0.1959462744

gβ€² 6 =β€‰βˆ’0.0107331755

h7 = 0.0036065536

g7 = 0.1273693403

hβ€² 7 = 0.1273693403

gβ€² 7 =β€‰βˆ’0.0036065536

h8 = 0.0332126741

g8 =β€‰βˆ’0.0930573646

hβ€² 8 = 0.0930573646

gβ€² 8 = 0.0332126741

h9 =β€‰βˆ’0.0294575368

g9 = βˆ’0.0713941472

hβ€² 9 =β€‰βˆ’0.0713941472

gβ€² 9 = 0.0294575368

h10 =β€‰βˆ’0.0713941472

g10 = 0.0294575368

hβ€² 10 =β€‰βˆ’0.0294575368

gβ€² 10 =β€‰βˆ’0.0713941472

h11 = 0.0930573646

g11 = 0.0332126741

hβ€² 11 = 0.0332126741

gβ€² 11 =β€‰βˆ’0.0930573646

h12 = 0.1273693403

g12 =β€‰βˆ’0.0036065536

hβ€² 12 = 0.0036065536

gβ€² 12 = 0.1273693403

h13 =β€‰βˆ’0.1959462744

g13 =β€‰βˆ’0.0107331755

hβ€² 13 =β€‰βˆ’0.0107331755

gβ€² 13 = 0.1959462744

h14 =β€‰βˆ’0.2498464243

g14 =β€‰βˆ’0.0013953517

hβ€² 14 = 0.0013953517

gβ€² 14 =β€‰βˆ’0.2498464243

h15 = 0.2811723437

g15 = 0.0019924053

hβ€² 15 = 0.0019924053

gβ€² 15 =β€‰βˆ’0.2811723437

h16 = 0.6884590395

g16 = 0.0006858567

hβ€² 16 =β€‰βˆ’0.0006858567

gβ€² 16 = 0.6884590395

h17 = 0.5272011889

g17 =β€‰βˆ’0.0001164669

hβ€² 17 =β€‰βˆ’0.0001164669

gβ€² 17 =β€‰βˆ’0.5272011889

h18 = 0.1881768001

g18 =β€‰βˆ’0.0000935887

hβ€² 18 = 0.0000935887

gβ€² 18 = 0.1881768001

h19 = 0.0266700579

g19 =β€‰βˆ’0.0000132642

hβ€² 19 =β€‰βˆ’0.0000132642

gβ€² 19 =β€‰βˆ’0.0266700579

β€˜db15’

h0 = 0.0000000613

g0 =β€‰βˆ’0.0045385374

hβ€² 0 = 0.0045385374

gβ€² 0 = 0.0000000613

h1 =β€‰βˆ’0.0000006317

g1 = 0.0467433949

hβ€² 1 = 0.0467433949

gβ€² 1 = 0.0000006317

h2 = 0.0000018113

g2 =β€‰βˆ’0.2060238640

hβ€² 2 = 0.2060238640

gβ€² 2 = 0.0000018113

h3 = 0.0000033630

g3 = 0.4926317717

hβ€² 3 = 0.4926317717

gβ€² 3 =β€‰βˆ’0.0000033630

h4 =β€‰βˆ’0.0000281333

g4 =β€‰βˆ’0.6458131404

hβ€² 4 = 0.6458131404

gβ€² 4 =β€‰βˆ’0.0000281333

h5 = 0.0000257927

g5 = 0.3390025355

hβ€² 5 = 0.3390025355

gβ€² 5 =β€‰βˆ’0.0000257927

h6 = 0.0001558965

g6 = 0.1932041396

hβ€² 6 =β€‰βˆ’0.1932041396

gβ€² 6 = 0.0001558965

h7 =β€‰βˆ’0.0003595652

g7 =β€‰βˆ’0.2888825966

hβ€² 7 =β€‰βˆ’0.2888825966

gβ€² 7 = 0.0003595652

h8 =β€‰βˆ’0.0003734824

g8 =β€‰βˆ’0.0652829528

hβ€² 8 = 0.0652829528

gβ€² 8 =β€‰βˆ’0.0003734824

h9 = 0.0019433240

g9 = 0.1901467140

hβ€² 9 = 0.1901467140

gβ€² 9 =β€‰βˆ’0.0019433240

h10 =β€‰βˆ’0.0002417565

g10 = 0.0396661766

hβ€² 10 =β€‰βˆ’0.0396661766

gβ€² 10 =β€‰βˆ’0.0002417565

h11 =β€‰βˆ’0.0064877346

g11 =β€‰βˆ’0.1111209360

hβ€² 11 =β€‰βˆ’0.1111209360

gβ€² 11 = 0.0064877346

h12 = 0.0051010004

g12 =β€‰βˆ’0.0338771439

hβ€² 12 = 0.0338771439

gβ€² 12 = 0.0051010004

h13 = 0.0150839180

g13 = 0.0547805506

hβ€² 13 = 0.0547805506

gβ€² 13 =β€‰βˆ’0.0150839180

h14 =β€‰βˆ’0.0208100502

g14 = 0.0257670073

hβ€² 14 =β€‰βˆ’0.0257670073

gβ€² 14 =β€‰βˆ’0.0208100502

h15 =β€‰βˆ’0.0257670073

g15 =β€‰βˆ’0.0208100502

hβ€² 15 =β€‰βˆ’0.0208100502

gβ€² 15 = 0.0257670073

h16 = 0.0547805506

g16 =β€‰βˆ’0.0150839180

hβ€² 16 = 0.0150839180

gβ€² 16 = 0.0547805506

h17 = 0.0338771439

g17 = 0.0051010004

hβ€² 17 = 0.0051010004

gβ€² 17 =β€‰βˆ’0.0338771439

h18 =β€‰βˆ’0.1111209360

g18 = 0.0064877346

hβ€² 18 =β€‰βˆ’0.0064877346

gβ€² 18 =β€‰βˆ’0.1111209360

h19 =β€‰βˆ’0.0396661766

g19 =β€‰βˆ’0.0002417565

hβ€² 19 = βˆ’0.0002417565

gβ€² 19 = 0.0396661766

h20 = 0.1901467140

g20 = βˆ’0.0019433240

hβ€² 20 = 0.0019433240

gβ€² 20 = 0.1901467140

h21 = 0.0652829528

g21 = βˆ’0.0003734824

hβ€² 21 = βˆ’0.0003734824

gβ€² 21 = βˆ’0.0652829528

h22 = βˆ’0.2888825966

g22 = 0.0003595652

hβ€² 22 = βˆ’0.0003595652

gβ€² 22 = βˆ’0.2888825966

h23 = βˆ’0.1932041396

g23 = 0.0001558965

hβ€² 23 = 0.0001558965

gβ€² 23 = 0.1932041396

h24 = 0.3390025355

g24 =β€‰βˆ’0.0000257927

hβ€² 24 = 0.0000257927

gβ€² 24 = 0.3390025355

h25 = 0.6458131404

g25 =β€‰βˆ’0.0000281333

hβ€² 25 =β€‰βˆ’0.0000281333

gβ€² 25 =β€‰βˆ’0.6458131404

h26 = 0.4926317717

g26 =β€‰βˆ’0.0000033630

hβ€² 26 = 0.0000033630

gβ€² 26 = 0.4926317717

h27 = 0.2060238640

g27 = 0.0000018113

hβ€² 27 = 0.0000018113

gβ€² 27 =β€‰βˆ’0.2060238640

h28 = 0.0467433949

g28 = 0.0000006317

hβ€² 28 =β€‰βˆ’0.0000006317

gβ€² 28 = 0.0467433949

h29 = 0.0045385374

g29 = 0.0000000613

hβ€² 29 = 0.0000000613

gβ€² 29 =β€‰βˆ’0.0045385374

coiflets 1

h0 =β€‰βˆ’0.0156557281

g0 = 0.0727326195

hβ€² 0 =β€‰βˆ’0.0727326195

gβ€² 0 =β€‰βˆ’0.0156557281

h1 =β€‰βˆ’0.0727326195

g1 = 0.3378976625

hβ€² 1 = 0.3378976625

gβ€² 1 = 0.0727326195

h2 = 0.3848648469

g2 =β€‰βˆ’0.8525720202

hβ€² 2 = 0.8525720202

gβ€² 2 = 0.3848648469

h3 = 0.8525720202

g3 = 0.3848648469

hβ€² 3 = 0.3848648469

gβ€² 3 =β€‰βˆ’0.8525720202

h4 = 0.3378976625

g4 = 0.0727326195

hβ€² 4 =β€‰βˆ’0.0727326195

gβ€² 4 = 0.3378976625

h5 =β€‰βˆ’0.0727326195

g5 =β€‰βˆ’0.0156557281

hβ€² 5 =β€‰βˆ’0.0156557281

gβ€² 5 = 0.0727326195

Biorthogonal 1.1

h0 = 0.7071067812

g0 =  =β€‰βˆ’0.7071067812

hβ€² 0 = 0.7071067812

gβ€² 0 = 0.7071067812

h1 = 0.7071067812

g1 = 0.7071067812

hβ€² 1 = 0.7071067812

gβ€² 1 =β€‰βˆ’0.7071067812

Reverse biorthogonal 1.1

h0 = 0.7071067812

g0 =β€‰βˆ’0.7071067812

hβ€² 0 = 0.7071067812

gβ€² 0 = 0.7071067812

h1 = 0.7071067812

g1 = 0.7071067812

hβ€² 1 = 0.7071067812

gβ€² 1 =β€‰βˆ’0.7071067812

Symlets 2

h0 =β€‰βˆ’0.1294095226

g0 =β€‰βˆ’0.4829629131

hβ€² 0 = 0.4829629131

gβ€² 0 =β€‰βˆ’0.1294095226

h1 = 0.2241438680

g1 = 0.8365163037

hβ€² 1 = 0.8365163037

gβ€² 1 =β€‰βˆ’0.2241438680

h2 = 0.8365163037

g2 =β€‰βˆ’0.2241438680

hβ€² 2 = 0.2241438680

gβ€² 2 = 0.8365163037

h3 = 0.4829629131

g3 =β€‰βˆ’0.1294095226

hβ€² 3 = βˆ’0.1294095226

gβ€² 3 =β€‰βˆ’0.4829629131

Discrete Meyer

h0 = 0

g0 = 0.0000000000

hβ€² 0 =β€‰βˆ’0.0000000000

gβ€² 0 = 0

h1 =β€‰βˆ’0.0000000000

g1 = 0.0000000085

hβ€² 1 = 0.0000000085

gβ€² 1 = 0.0000000000

h2 = 0.0000000085

g2 = 0.0000000111

hβ€² 2 =β€‰βˆ’0.0000000111

gβ€² 2 = 0.0000000085

h3 =β€‰βˆ’0.0000000111

g3 =β€‰βˆ’0.0000000108

hβ€² 3 =β€‰βˆ’0.0000000108

gβ€² 3 = 0.0000000111

h4 =β€‰βˆ’0.0000000108

g4 =β€‰βˆ’0.0000000607

hβ€² 4 = 0.0000000607

gβ€² 4 =β€‰βˆ’0.0000000108

h5 = 0.0000000607

g5 =β€‰βˆ’0.0000001087

hβ€² 5 =β€‰βˆ’0.0000001087

gβ€² 5 =β€‰βˆ’0.0000000607

h6 =β€‰βˆ’0.0000001087

g6 =β€‰βˆ’0.0000000820

hβ€² 6 = 0.0000000820

gβ€² 6 =β€‰βˆ’0.0000001087

h7 = 0.0000000820

g7 = 0.0000001178

hβ€² 7 = 0.0000001178

gβ€² 7 =β€‰βˆ’0.0000000820

h8 = 0.0000001178

g8 = 0.0000005506

hβ€² 8 =β€‰βˆ’0.0000005506

gβ€² 8 = 0.0000001178

h9 =β€‰βˆ’0.0000005506

g9 = 0.0000011308

hβ€² 9 = 0.0000011308

gβ€² 9 = 0.0000005506

h10 = 0.0000011308

g10 = 0.0000014895

hβ€² 10 =β€‰βˆ’0.0000014895

gβ€² 10 = 0.0000011308

h11 =β€‰βˆ’0.0000014895

g11 = 0.0000007368

hβ€² 11 = 0.0000007368

gβ€² 11 = 0.0000014895

h12 = 0.0000007368

g12 =βˆ’0.0000032054

hβ€² 12 = 0.0000032054

gβ€² 12 = 0.0000007368

h13 = 0.0000032054

g13 =β€‰βˆ’0.0000163127

hβ€² 13 =β€‰βˆ’0.0000163127

gβ€² 13 =β€‰βˆ’0.0000032054

h14 =β€‰βˆ’0.0000163127

g14 =β€‰βˆ’0.0000655431

hβ€² 14 = 0.0000655431

gβ€² 14 =β€‰βˆ’0.0000163127

h15 = 0.0000655431

g15 =β€‰βˆ’0.0006011502

hβ€² 15 =β€‰βˆ’0.0006011502

gβ€² 15 =β€‰βˆ’0.0000655431

h16 =β€‰βˆ’0.0006011502

g16 = 0.0027046721

hβ€² 16 =β€‰βˆ’0.0027046721

gβ€² 16 =β€‰βˆ’0.0006011502

h17 =β€‰βˆ’0.0027046721

g17 = 0.0022025341

hβ€² 17 = 0.0022025341

gβ€² 17 = 0.0027046721

h18 = 0.0022025341

g18 =β€‰βˆ’0.0060458141

hβ€² 18 = 0.0060458141

gβ€² 18 = 0.0022025341

h19 = 0.0060458141

g19 =β€‰βˆ’0.0063877183

hβ€² 19 =β€‰βˆ’0.0063877183

gβ€² 19 =β€‰βˆ’0.0060458141

h20 =β€‰βˆ’0.0063877183

g20 = 0.0110614964

hβ€² 20 =β€‰βˆ’0.0110614964

gβ€² 20 =β€‰βˆ’0.0063877183

h21 =β€‰βˆ’0.0110614964

g21 = 0.0152700151

hβ€² 21 = 0.0152700151

gβ€² 21 = 0.0110614964

h22 = 0.0152700151

g22 =β€‰βˆ’0.0174234341

hβ€² 22 = 0.0174234341

gβ€² 22 = 0.0152700151

h23 = 0.0174234341

g23 =β€‰βˆ’0.0321307940

hβ€² 23 =β€‰βˆ’0.0321307940

gβ€² 23 =β€‰βˆ’0.0174234341

h24 =β€‰βˆ’0.0321307940

g24 = 0.0243487459

hβ€² 24 =β€‰βˆ’0.0243487459

gβ€² 24 =β€‰βˆ’0.0321307940

h25 =β€‰βˆ’0.0243487459

g25 = 0.0637390243

hβ€² 25 = 0.0637390243

gβ€² 25 = 0.0243487459

h26 = 0.0637390243

g26 =β€‰βˆ’0.0306550920

hβ€² 26 = 0.0306550920

gβ€² 26 = 0.0637390243

h27 = 0.0306550920

g27 =β€‰βˆ’0.1328452004

hβ€² 27 =β€‰βˆ’0.1328452004

gβ€² 27 =β€‰βˆ’0.0306550920

h28 =β€‰βˆ’0.1328452004

g28 = 0.0350875557

hβ€² 28 =β€‰βˆ’0.0350875557

gβ€² 28 =β€‰βˆ’0.1328452004

h29 =β€‰βˆ’0.0350875557

g29 = 0.4445930028

hβ€² 29 = 0.4445930028

gβ€² 29 = 0.0350875557

h30 = 0.4445930028

g30 =β€‰βˆ’0.7445855923

hβ€² 30 = 0.7445855923

gβ€² 30 = 0.4445930028

h31 = 0.7445855923

g31 = 0.4445930028

hβ€² 31 = 0.4445930028

gβ€² 31 =β€‰βˆ’0.7445855923

h32 = 0.4445930028

g32 = 0.0350875557

hβ€² 32 =β€‰βˆ’0.0350875557

gβ€² 32 = 0.4445930028

h33 =β€‰βˆ’0.0350875557

g33 =β€‰βˆ’0.1328452004

hβ€² 33 =β€‰βˆ’0.1328452004

gβ€² 33 = 0.0350875557

h34 =β€‰βˆ’0.1328452004

g34 =β€‰βˆ’0.0306550920

hβ€² 34 = 0.0306550920

gβ€² 34 =β€‰βˆ’0.1328452004

h35 = 0.0306550920

g35 = 0.0637390243

hβ€² 35 = 0.0637390243

gβ€² 35 =β€‰βˆ’0.0306550920

h36 = 0.0637390243

g36 = 0.0243487459

hβ€² 36 =β€‰βˆ’0.0243487459

gβ€² 36 = 0.0637390243

h37 =β€‰βˆ’0.0243487459

g37 =β€‰βˆ’0.0321307940

hβ€² 37 =β€‰βˆ’0.0321307940

gβ€² 37 = 0.0243487459

h38 =β€‰βˆ’0.0321307940

g38 =β€‰βˆ’0.0174234341

hβ€² 38 = 0.0174234341

gβ€² 38 =β€‰βˆ’0.0321307940

h39 = 0.0174234341

g39 = 0.0152700151

hβ€² 39 = 0.0152700151

gβ€² 39 =β€‰βˆ’0.0174234341

h40 = 0.0152700151

g40 = 0.0110614964

hβ€² 40 =β€‰βˆ’0.0110614964

gβ€² 40 = 0.0152700151

h41 =β€‰βˆ’0.0110614964

g41 =β€‰βˆ’0.0063877183

hβ€² 41 =β€‰βˆ’0.0063877183

gβ€² 41 = 0.0110614964

h42 =β€‰βˆ’0.0063877183

g42 =β€‰βˆ’0.0060458141

hβ€² 42 = 0.0060458141

gβ€² 42 =β€‰βˆ’0.0063877183

h43 = 0.0060458141

g43 = 0.0022025341

hβ€² 43 = 0.0022025341

gβ€² 43 =β€‰βˆ’0.0060458141

h44 = 0.0022025341

g44 = 0.0027046721

hβ€² 44 =β€‰βˆ’0.0027046721

gβ€² 44 = 0.0022025341

h45 =β€‰βˆ’0.0027046721

g45 =β€‰βˆ’0.0006011502

hβ€² 45 =β€‰βˆ’0.0006011502

gβ€² 45 = 0.0027046721

h46 =β€‰βˆ’0.0006011502

g46 =β€‰βˆ’0.0000655431

hβ€² 46 =β€‰βˆ’0.0000655431

gβ€² 46 =β€‰βˆ’0.0006011502

h47 = 0.0000655431

g47 =β€‰βˆ’0.0000163127

hβ€² 47 =β€‰βˆ’0.0000163127

gβ€² 47 =β€‰βˆ’0.0000655431

h48 =β€‰βˆ’0.0000163127

g48 =β€‰βˆ’0.0000032054

hβ€² 48 = 0.0000032054

gβ€² 48 =β€‰βˆ’0.0000163127

h49 = 0.0000032054

g49 = 0.0000007368

hβ€² 49 = 0.0000007368

gβ€² 49 =β€‰βˆ’0.0000032054

h50 = 0.0000007368

g50 = 0.0000014895

hβ€² 50 =β€‰βˆ’0.0000014895

gβ€² 50 = 0.0000007368

h51 =β€‰βˆ’0.0000014895

g51 = 0.0000011308

hβ€² 51 = 0.0000011308

gβ€² 51 = 0.0000014895

h52 = 0.0000011308

g52 = 0.0000005506

hβ€² 52 =β€‰βˆ’0.0000005506

gβ€² 52 = 0.0000011308

h53 =β€‰βˆ’0.0000005506

g53 = 0.0000001178

hβ€² 53 = 0.0000001178

gβ€² 53 =β€‰βˆ’0.0000005506

h54 = 0.0000001178

g54 =β€‰βˆ’0.0000000820

hβ€² 54 = 0.0000000820

gβ€² 54 = 0.0000001178

h55 = 0.0000000820

g55 =β€‰βˆ’0.0000001087

hβ€² 55 =β€‰βˆ’0.0000001087

gβ€² 55 =β€‰βˆ’0.0000000820

h56 =β€‰βˆ’0.0000001087

g56 =β€‰βˆ’0.0000000607

hβ€² 56 = 0.0000000607

gβ€² 56 =β€‰βˆ’0.0000001087

h57 = 0.0000000607

g57 =β€‰βˆ’0.0000000108

hβ€² 57 =β€‰βˆ’0.0000000108

gβ€² 57 =β€‰βˆ’0.0000000607

h58 =β€‰βˆ’0.0000000108

g58 = 0.0000000111

hβ€² 58 =β€‰βˆ’0.0000000111

gβ€² 58 =β€‰βˆ’0.0000000108

h59 =β€‰βˆ’0.0000000111

g59 = 0.0000000085

hβ€² 59 = 0.0000000085

gβ€² 59 = 0.0000000111

h60 = 0.0000000085

g60 = 0.0000000000

hβ€² 60 =β€‰βˆ’0.0000000000

gβ€² 60 = 0.0000000085

h61 =β€‰βˆ’0.0000000000

g61 = 0

hβ€² 61 = 0

gβ€² 61 = 0.0000000000

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Mataei, B., Zakeri, H. & Nejad, F.M. An Overview of Multiresolution Analysis for Nondestructive Evaluation of Pavement Surface Drainage. Arch Computat Methods Eng 26, 143–161 (2019). https://doi.org/10.1007/s11831-017-9230-7

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  • DOI: https://doi.org/10.1007/s11831-017-9230-7

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