Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards MyNewsletter Firmensuche
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
Sustainability in Automotive

Gesamtlebenszyklus wird immer wichtiger

In der Digitalkonferenz am 5. Dezember 2024 geht es um die wachsende Bedeutung der Kreislaufwirtschaft in der Automobilindustrie und wie nachhaltige Werkstoffe sowie wiederverwendbare Komponenten dazu beitragen können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

A Review on Infrared and Visible Image Fusion Techniques

verfasst von : Ami Patel, Jayesh Chaudhary

Erschienen in: Intelligent Communication Technologies and Virtual Mobile Networks

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The term fusion means in moderate approach to extract the information acquired in several domains. The term infrared and visible image fusion has been intended to find compatible fused image with detailed textures of visible images and an impressive infrared object area. We therefore combine infrared and visible images to create solitary image. Current real - time applications that encourage image fusion including military surveillance, automate agricultural, object recognition, remote sensing, and medical applications. The concept of merging two or more than two images using the various image fusion schemes. This paper begins with the background information on the image fusion. Secondly, infrared and visible image fusion rest on multi-scale transformation of existing techniques are reviewed with all the merits and demerits of the same table lists. Further section elaborates fusion strategies and fusion performance evaluation metrics are summarized.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren
Vorheriges Kapitel Algo_Seer: System for Extracting and Searching Algorithms in Scholarly Big Data
Nächstes Kapitel Implementation of the Standard Floating Point DWT Using IEEE 754 Floating Point MAC
Literatur
1.
Ma, J., Ma, Y., Li, C.: Infrared and visible image fusion methods and applications: a survey. Inf. Fusion 45, 153–178 (2018)CrossRef
2.
Jin, X., Jiang, Q., Yao, S., Zhou, D., Nie, R., Hai, J., He, K.: A survey of infrared and visual image fusion methods. Infrared Phys. Technol. 85, 478–501 (2017)CrossRef
3.
Dogra, A., Goyal, B., Agrawal, S.: From multi-scale decomposition to non-multi-scale decomposition methods: a comprehensive survey of image fusion techniques and its applications. IEEE Access 5, 16040–16067 (2017)CrossRef
4.
Yu, X., Ren, J., Chen, Q., Sui, X.: A false color image fusion method based on multi-resolution color transfer in normalization YCBCR space. Optik – Int. J. Light Electron Opt. 125(20), 6010–6016 (2014)CrossRef
5.
Liu, Z., Tsukada, K., Hanasaki, K., Ho, Y., Dai, Y.: Image fusion by using steerable pyramid. Pattern Recogn. Lett. 22(9), 929–939 (2001)CrossRef
6.
Xu, H., Wang, Y., Wu, Y., Qian, Y.: Infrared and multi-type images fusion algorithm based on contrast pyramid transform. Infrared Phys. Technol. 78, 133–146 (2016)CrossRef
7.
Zhan, L., Zhuang, Y., Huang, L.: Infrared and visible images fusion method based on discrete wavelet transform. J. Comput. 28, 57–71 (2017)
8.
Madheswari, K., Venkateswaran, N.: Swarm intelligence based optimisation in thermal image fusion using dual tree discrete wavelet transform. Quant. InfraRed Thermography J. 14(1), 24–43 (2016)CrossRef
9.
Zou, Y., Liang, X., Wang, T.: Visible and infrared image fusion using the lifting wavelet. TELKOMNIKA Indonesian J. Electr. Eng. 11 (2013)
10.
Yan, X., Qin, H., Li, J., Zhou, H., Zong, J.-G.: Infrared and visible image fusion with spectral graph wavelet transform. J. Opt. Soc. Am. A 32, 1643 (2015)CrossRef
11.
Chai, P., Luo, X., Zhang, Z.: Image fusion using quaternion wavelet transform and multiple features. IEEE Access 5, 6724–6734 (2017)CrossRef
12.
Quan, S., Qian, W., Guo, J., Zhao, H.: Visible and infrared image fusion based on curvelet transform. In: International Conference on Systems and Informatics (ICSAI) (2014)
13.
Li, H., Liu, L., Huang, W., Yue, C.: An improved fusion algorithm for infrared and visible images based on multi-scale transform. Infrared Phys. Technol. 74, 28–37 (2016)CrossRef
14.
Bavirisetti, D.P., Dhuli, R.: Two-scale image fusion of visible and infrared images using saliency detection. Infrared Phys. Technol. 76, 52–64 (2016)CrossRef
15.
Yan, X., Qin, H., Li, J., Zhou, H., Zong, J.-G., Zeng, Q.: Infrared and visible image fusion using multiscale directional nonlocal means filter. Appl. Opt. 54(13), 4299 (2015)CrossRef
16.
Bavirisetti, D.P., Dhuli, R.: Fusion of infrared and visible sensor images based on anisotropic diffusion and Karhunen-Loeve transform. IEEE Sens. J. 16(1), 203–209 (2016)CrossRef
17.
Hu, J., Li, S.: The multiscale directional bilateral filter and its application to multisensor image fusion. Inf. Fusion 13(3), 196–206 (2012)CrossRef
18.
Toet, A., Hogervorst, M.A.: Multiscale image fusion through guided filtering. In: Target and Background Signatures II (2016)
19.
Yang, B., Jing, Z.-L., Zhao, H.-T.: Review of pixel-level image fusion. J. Shanghai Jiaotong Univ. (Sci.) 15(1), 6–12 (2010)CrossRef
20.
Piella, G.: A general framework for multiresolution image fusion: from pixels to regions. Inf. Fusion 4(4), 259–280 (2003)CrossRef
21.
Kalaivani, K., Phamila, Y.A.V.: Analysis of image fusion techniques based on quality assessment metrics. Indian J. Sci. Technol. 9(31), 1–8 (2016)CrossRef
22.
Meng, F., Song, M., Guo, B., Shi, R., Shan, D.: Image fusion based on object region detection and non-subsampled contourlet transform. Comput. Electr. Eng. 62, 375–383 (2017)CrossRef
23.
Wu, W., Qiu, Z., Zhao, M., Huang, Q., Lei, Y.: Visible and infrared image fusion using NSST and deep Boltzmann machine. Optik 157, 334–342 (2018)CrossRef
24.
Paramanandham, N., Rajendiran, K.: Infrared and visible image fusion using discrete cosine transform and swarm intelligence for surveillance applications. Infrared Phys. Technol. 88, 13–22 (2018)CrossRef
25.
Bai, X., Zhou, F., Xue, B.: Fusion of infrared and visual images through region extraction by using multi scale center-surround top-hat transform. Opt. Express 19(9), 8444 (2011)CrossRef
26.
Song, Y., Xiao, J., Yang, J., Chai, Z., Wu, Y.: Research on MR-SVD based visual and infrared image fusion. In: Infrared Technology and Applications, and Robot Sensing and Advanced Control (2016)
27.
Falk, H.H.: Prolog to a categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application. Proc. IEEE 87(8), 1313–1314 (1999)CrossRef
28.
Metadaten
Titel
A Review on Infrared and Visible Image Fusion Techniques
verfasst von
Ami Patel
Jayesh Chaudhary
Copyright-Jahr
2020
Buch
Intelligent Communication Technologies and Virtual Mobile Networks

Print ISBN: 978-3-030-28363-6

Electronic ISBN: 978-3-030-28364-3

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-28364-3_12