Skip to main content
Top

2019 | OriginalPaper | Chapter

2. Technical Information

Authors : Rohit Thanki, Surekha Borra

Published in: Medical Imaging and its Security in Telemedicine Applications

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter presents various image transforms which are used in the present research work. This chapter also describes different encryption methods such as compressive sensing (CS)-based encryption and Arnold scrambling. Finally, some noise sequences used in the presented technique are described.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Jain A (1999) Fundamentals of digital image processing. Prentice Hall Inc, Upper Saddle River, NJMATH Jain A (1999) Fundamentals of digital image processing. Prentice Hall Inc, Upper Saddle River, NJMATH
2.
go back to reference Yan J (2009) Wavelet matrix. Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC Yan J (2009) Wavelet matrix. Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC
3.
go back to reference Vidakovic B (1999) Statistical modelling by wavelets. Wiley, New York, pp 115–116CrossRef Vidakovic B (1999) Statistical modelling by wavelets. Wiley, New York, pp 115–116CrossRef
4.
go back to reference Hiena T, Nakaoa Z, Chen Y (2006) Robust multi-logo watermarking by RDWT and ICA. Signal Process 86:2981–2993CrossRef Hiena T, Nakaoa Z, Chen Y (2006) Robust multi-logo watermarking by RDWT and ICA. Signal Process 86:2981–2993CrossRef
5.
go back to reference Lagzian S, Soryani M, Fathy M (2011) A new robust watermarking scheme based on RDWT – SVD. Int J Intell Inf Process 2(1):22–29 Lagzian S, Soryani M, Fathy M (2011) A new robust watermarking scheme based on RDWT – SVD. Int J Intell Inf Process 2(1):22–29
6.
7.
go back to reference Candes E, Donoho DL (2004) New tight frames of curvelets and optimal representations of objects with piecewise-C2 singularities. Commun Pure Appl Math 57:219–266CrossRef Candes E, Donoho DL (2004) New tight frames of curvelets and optimal representations of objects with piecewise-C2 singularities. Commun Pure Appl Math 57:219–266CrossRef
9.
go back to reference Do M, Vetterli M (2000) Orthonormal finite ridgelet transform for image compression. In: Proceedings of the international conference on image processing (ICIP ’00), pp 367–370 Do M, Vetterli M (2000) Orthonormal finite ridgelet transform for image compression. In: Proceedings of the international conference on image processing (ICIP ’00), pp 367–370
10.
go back to reference Candes E, Donoho D (2000) A surprisingly effective non-adaptive representation for objects with edges, curves and surfaces. Vanderbilt University Press, Nashville, TN Candes E, Donoho D (2000) A surprisingly effective non-adaptive representation for objects with edges, curves and surfaces. Vanderbilt University Press, Nashville, TN
11.
go back to reference Candes E (1998) Ridgelets theory and application. Ph.D. Thesis, Department of Statistics, Stanford University, Stanford, CA Candes E (1998) Ridgelets theory and application. Ph.D. Thesis, Department of Statistics, Stanford University, Stanford, CA
12.
go back to reference AlZubi S, Islam N, Abbod M (2011) Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation. Int J Biomed Imaging 2011:18CrossRef AlZubi S, Islam N, Abbod M (2011) Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation. Int J Biomed Imaging 2011:18CrossRef
13.
go back to reference Candes E, Donoho D (1999) Ridgelets: a key to higher dimensional intermittency? Phil Trans R Soc A 357(1760):2495–2509MathSciNetCrossRef Candes E, Donoho D (1999) Ridgelets: a key to higher dimensional intermittency? Phil Trans R Soc A 357(1760):2495–2509MathSciNetCrossRef
14.
go back to reference He J (2006) A characterization of inverse Radon transform on the Laguerre hypergroup. J Math Anal Appl 318(1):387–395MathSciNetCrossRef He J (2006) A characterization of inverse Radon transform on the Laguerre hypergroup. J Math Anal Appl 318(1):387–395MathSciNetCrossRef
15.
go back to reference Dettori L, Semler L (2007) A comparison of wavelet, ridgelet and curvelet-based texture classification algorithms in computed tomography. Comput Biol Med 37(4):486–498CrossRef Dettori L, Semler L (2007) A comparison of wavelet, ridgelet and curvelet-based texture classification algorithms in computed tomography. Comput Biol Med 37(4):486–498CrossRef
16.
go back to reference Do M, Vetterli M (2005) The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans Image Process 14(12):2091–2106CrossRef Do M, Vetterli M (2005) The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans Image Process 14(12):2091–2106CrossRef
17.
go back to reference Da Cunha AL, Zhou J, Do MN (2006) The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans Image Process 15(10):3089–3101CrossRef Da Cunha AL, Zhou J, Do MN (2006) The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans Image Process 15(10):3089–3101CrossRef
18.
go back to reference Arnold VI, Avez A (1968) Ergodic problems in classical mechanics. Benjamin, New YorkMATH Arnold VI, Avez A (1968) Ergodic problems in classical mechanics. Benjamin, New YorkMATH
20.
go back to reference Candes E, Wakin M (2008) An introduction to compressive sampling. IEEE Signal Process Mag 25(2):21–30CrossRef Candes E, Wakin M (2008) An introduction to compressive sampling. IEEE Signal Process Mag 25(2):21–30CrossRef
21.
go back to reference Rachlin Y, Baron D (2008) The secrecy of compressed sensing measurements. In: The 46th Annual Allerton conference on communication, control, and computing. IEEE, pp 813–817 Rachlin Y, Baron D (2008) The secrecy of compressed sensing measurements. In: The 46th Annual Allerton conference on communication, control, and computing. IEEE, pp 813–817
22.
go back to reference Orsdemir A, Altun HO, Sharma G, Bocko MF (2008) On the security and robustness of encryption via compressed sensing. In: 2008 I.E. military communications conference. MILCOM 2008. IEEE, pp 1–7 Orsdemir A, Altun HO, Sharma G, Bocko MF (2008) On the security and robustness of encryption via compressed sensing. In: 2008 I.E. military communications conference. MILCOM 2008. IEEE, pp 1–7
23.
go back to reference Agrawal S, Vishwanath S (2011) Secrecy using compressive sensing. In: 2011 I.E. information theory workshop (ITW). IEEE, pp 563–567 Agrawal S, Vishwanath S (2011) Secrecy using compressive sensing. In: 2011 I.E. information theory workshop (ITW). IEEE, pp 563–567
24.
go back to reference Hossein SA, Tabatabaei AE, Zivic N (2012) Security analysis of the joint encryption and compressed sensing. In: 2012 20th telecommunications forum (TELFOR). IEEE, pp 799–802 Hossein SA, Tabatabaei AE, Zivic N (2012) Security analysis of the joint encryption and compressed sensing. In: 2012 20th telecommunications forum (TELFOR). IEEE, pp 799–802
25.
go back to reference Zhang Y, Zhang LY, Zhou J, Liu L, Chen F, He X (2016) A review of compressive sensing in information security field. IEEE Access 4:2507–2519CrossRef Zhang Y, Zhang LY, Zhou J, Liu L, Chen F, He X (2016) A review of compressive sensing in information security field. IEEE Access 4:2507–2519CrossRef
26.
go back to reference Tropp JA, Gilbert AC (2007) Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inf Theory 53(12):4655–4666MathSciNetCrossRef Tropp JA, Gilbert AC (2007) Signal recovery from random measurements via orthogonal matching pursuit. IEEE Trans Inf Theory 53(12):4655–4666MathSciNetCrossRef
27.
go back to reference Borra S, Thanki R, Dey N, Borisagar K (2018) Secure transmission and integrity verification of color radiological images using fast discrete curvelet transform and compressive sensing. Smart Health. Borra S, Thanki R, Dey N, Borisagar K (2018) Secure transmission and integrity verification of color radiological images using fast discrete curvelet transform and compressive sensing. Smart Health.
28.
go back to reference Mancini C, Bruce R (2009) OP amps for everyone. Texas Instruments, pp 10–11 Mancini C, Bruce R (2009) OP amps for everyone. Texas Instruments, pp 10–11
Metadata
Title
Technical Information
Authors
Rohit Thanki
Surekha Borra
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-319-93311-5_2