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Low complexity multifocus image fusion in discrete cosine transform domain

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Języki publikacji
EN
Abstrakty
EN
This paper presents a low complex, highly energy efficient sensor image fusion scheme explicitly designed for wireless visual sensor systems equipped with resource constrained, battery powered image sensors and employed in surveillance, hazardous environment like battlefields etc. Here an energy efficient simple method for fusion of multifocus images based on higher valued AC coefficients calculated in discrete cosine transform domain is presented. The proposed method overcomes the computation and energy limitation of low power devices and is investigated in terms of image quality and computation energy. Simulations are performed using Atmel ATmega128 processor of Mica 2 mote, to measure the resultant energy savings and the simulation results demonstrate that the proposed algorithm is extremely fast and consumes only around 1% of energy consumed by conventional discrete cosine transform based fusion schemes. Also the simplicity of our proposed method makes it more appropriate for real-time applications.
Czasopismo
Rocznik
Strony
693--706
Opis fizyczny
Bibliogr. 22 poz., rys., wykr. tab.
Twórcy
autor
  • Department of Electronics and Communication Engineering, SSN College of Engineering, SSN Nagar, Chennai, India – 603110
autor
  • Department of Electronics and Communication Engineering, SSN College of Engineering, SSN Nagar, Chennai, India – 603110
Bibliografia
  • [1] DRAJIC D., CVEJIC N., Adaptive fusion of multimodal surveillance image sequences in visual sensor networks, IEEE Transactions on Consumer Electronics 53(4), 2007, pp. 1456–1462.
  • [2] SHUTAO LI, BIN YANG, Multifocus image fusion using region segmentation and spatial frequency, Image and Vision Computing 26(7), 2008 , pp. 971–979.
  • [3] JING TIAN, LI CHEN, Adaptive multi-focus image fusion using a wavelet-based statistical sharpness measure, Signal Processing 92(9), 2012, pp. 2137–2146.
  • [4] MOHAMMAD BAGHER AKBARI HAGHIGHAT, ALI AGHAGOLZADEH, HADI SEYEDARABI, Multi-focus image fusion for visual sensor networks in DCT domain, Computers and Electrical Engineering 37(5), 2011, pp. 789–797.
  • [5] JINSHAN TANG, A contrast based image fusion technique in the DCT domain, Digital Signal Processing 14(3), 2004, pp. 218–226.
  • [6] HOSSNY M., NAHAVANDI S., CREIGHTON D., BHATTI A., Towards autonomous image fusion, [In] 11th International Conference on Control Automation Robotics and Vision (ICARCV), 2010, pp. 1748–1754.
  • [7] JIE LIANG, TRAN T.D., Fast multiplierless approximations of the DCT with the lifting scheme, IEEE Transactions on Signal Processing 49(12), 2001, pp. 3032–3044.
  • [8] LECUIRE V., MAKKAOUI L., MOUREAUX J.M., Fast zonal DCT for energy conservation in wireless image sensor networks, Electronics Letters 48(2), 2012, pp. 125–127.
  • [9] http://decsai.ugr.es/cvg/CG/base.htm
  • [10] http://links.uwaterloo.ca/Repository.html
  • [11] http://www.imagefusion.org
  • [12] http://www.mathworks.com/matlabcentral/fileexchange/40861
  • [13] LI H., MANJUNATH B.S., MITRA S.K., Multisensor image fusion using the wavelet transform, Graphical Models and Image Processing 57(3), 1995, pp. 235–245.
  • [14] ROCKINGER O., Image sequence fusion using a shift-invariant wavelet transform, [In] International Conference on Image Processing – Proceedings, Vol. 3, 1997, pp. 288–291.
  • [15] http://www.metapix.de/toolbox.htm
  • [16] ZHOU WANG, BOVIK A.C., SHEIKH H.R., SIMONCELLI E.P., Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing 13(4), 2004, pp. 600–612.
  • [17] XIANGZHI BAI, FUGEN ZHOU, BINDANG XUE, Edge preserved image fusion based on multiscale toggle contrast operator, Image and Vision Computing 29(12), 2011, pp. 829–839.706 A.V. PHAMILA, R. AMUTHA
  • [18] XYDEAS C.S., PETROVIC V., Objective image fusion performance measure, Electronics Letters 36(4), 2000, pp. 308–309.
  • [19] PETROVIC V., COOTES T., Objectively optimised multisensor image fusion, [In] Proceedings of 9th International Conference on Information Fusion, 2006, pp. 1–7.
  • [20] GUIHONG QU, DALI ZHANG, PINGFAN YAN, Information measure for performance of image fusion, Electronics Letters 38(7), 2002, pp. 313–315.
  • [21] MOHAMMAD BAGHER AKBARI HAGHIGHAT, ALI AGHAGOLZADEH, HADI SEYEDARABI, A non-reference image fusion metric based on mutual information of image features, Computers and Electrical Engineering 37(5), 2011, pp. 744–756.
  • [22] DONG-U LEE, HYUNGJIN KIM, RAHIMI M., ESTRIN D., VILLASENOR J.D., Energy-efficient image compression for resource-constrained platforms, IEEE Transactions on Image Processing 18(9), 2009, pp. 2100–2113.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-291a68ca-0747-405c-b334-1d23449141d9
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