IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v416y2014icp400-410.html
   My bibliography  Save this article

Optimized Laplacian image sharpening algorithm based on graphic processing unit

Author

Listed:
  • Ma, Tinghuai
  • Li, Lu
  • Ji, Sai
  • Wang, Xin
  • Tian, Yuan
  • Al-Dhelaan, Abdullah
  • Al-Rodhaan, Mznah

Abstract

In classical Laplacian image sharpening, all pixels are processed one by one, which leads to large amount of computation. Traditional Laplacian sharpening processed on CPU is considerably time-consuming especially for those large pictures. In this paper, we propose a parallel implementation of Laplacian sharpening based on Compute Unified Device Architecture (CUDA), which is a computing platform of Graphic Processing Units (GPU), and analyze the impact of picture size on performance and the relationship between the processing time of between data transfer time and parallel computing time. Further, according to different features of different memory, an improved scheme of our method is developed, which exploits shared memory in GPU instead of global memory and further increases the efficiency. Experimental results prove that two novel algorithms outperform traditional consequentially method based on OpenCV in the aspect of computing speed.

Suggested Citation

  • Ma, Tinghuai & Li, Lu & Ji, Sai & Wang, Xin & Tian, Yuan & Al-Dhelaan, Abdullah & Al-Rodhaan, Mznah, 2014. "Optimized Laplacian image sharpening algorithm based on graphic processing unit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 400-410.
    • Handle: RePEc:eee:phsmap:v:416:y:2014:i:c:p:400-410
    DOI: 10.1016/j.physa.2014.09.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114007845
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2014.09.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kilic, Ilker & Kayacan, Ozhan, 2012. "Generalized ICM for image segmentation based on Tsallis statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4899-4908.
    2. Florindo, João B. & Sikora, Mariana S. & Pereira, Ernesto C. & Bruno, Odemir M., 2013. "Characterization of nanostructured material images using fractal descriptors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1694-1701.
    3. Sheppard, Adrian P. & Sok, Robert M. & Averdunk, Holger, 2004. "Techniques for image enhancement and segmentation of tomographic images of porous materials," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 145-151.
    4. Vandembroucq, Damien & Roux, Stéphane, 2005. "Laplacian transfer across a rough interface: numerical resolution in the conformal plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 357(1), pages 97-102.
    5. Barbieri, Andre L. & de Arruda, G.F. & Rodrigues, Francisco A. & Bruno, Odemir M. & Costa, Luciano da Fontoura, 2011. "An entropy-based approach to automatic image segmentation of satellite images," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(3), pages 512-518.
    6. Zhan, Choujun & Chen, Guanrong & Yeung, Lam F., 2010. "On the distributions of Laplacian eigenvalues versus node degrees in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1779-1788.
    7. Wei, Jianming, 2014. "A parallel Monte Carlo method for population balance modeling of particulate processes using bookkeeping strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 186-197.
    8. Kiwata, Hirohito, 2012. "Physical consideration of an image in image restoration using Bayes’ formula," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2215-2224.
    9. Leyva, J. Francisco & Málaga, Carlos & Plaza, Ramón G., 2013. "The effects of nutrient chemotaxis on bacterial aggregation patterns with non-linear degenerate cross diffusion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5644-5662.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lahmiri, Salim, 2016. "Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 235-243.
    2. Shuangmei Zou & Peixing Xu & Congjiao Xie & Xuan Deng & Haodong Tang, 2022. "Characterization of Two-Phase Flow from Pore-Scale Imaging Using Fractal Geometry under Water-Wet and Mixed-Wet Conditions," Energies, MDPI, vol. 15(6), pages 1-17, March.
    3. Gonçalves, Wesley Nunes & Machado, Bruno Brandoli & Bruno, Odemir Martinez, 2014. "Texture descriptor combining fractal dimension and artificial crawlers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 358-370.
    4. Fabbri, Ricardo & Gonçalves, Wesley N. & Lopes, Francisco J.P. & Bruno, Odemir M., 2012. "Multi-q pattern analysis: A case study in image classification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(19), pages 4487-4496.
    5. Soares, H.C. & Meireles, J.B. & Castro, A.O. & Huguenin, J.A.O. & Schmidt, A.G.M. & da Silva, L., 2015. "Tsallis threshold analysis of digital speckle patterns generated by rough surfaces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 1-8.
    6. Jones, A.C. & Sheppard, A.P. & Sok, R.M. & Arns, C.H. & Limaye, A. & Averdunk, H. & Brandwood, A. & Sakellariou, A. & Senden, T.J. & Milthorpe, B.K. & Knackstedt, M.A., 2004. "Three-dimensional analysis of cortical bone structure using X-ray micro-computed tomography," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 125-130.
    7. Turner, M.L. & Knüfing, L. & Arns, C.H. & Sakellariou, A. & Senden, T.J. & Sheppard, A.P. & Sok, R.M. & Limaye, A. & Pinczewski, W.V. & Knackstedt, M.A., 2004. "Three-dimensional imaging of multiphase flow in porous media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 166-172.
    8. Sakellariou, A. & Sawkins, T.J. & Senden, T.J. & Limaye, A., 2004. "X-ray tomography for mesoscale physics applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 152-158.
    9. Aste, T. & Saadatfar, M. & Sakellariou, A. & Senden, T.J., 2004. "Investigating the geometrical structure of disordered sphere packings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(1), pages 16-23.
    10. Deyasi, Krishanu & Chakraborty, Abhijit & Banerjee, Anirban, 2017. "Network similarity and statistical analysis of earthquake seismic data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 224-234.
    11. Cruz-García, S. & Martínez-Farías, F. & Santillán-Hernández, A.S. & Rangel, E., 2021. "Mathematical home burglary model with stochastic long crime trips and patrolling: Applied to Mexico City," Applied Mathematics and Computation, Elsevier, vol. 396(C).
    12. Florindo, J.B. & Bruno, O.M., 2016. "Texture analysis by fractal descriptors over the wavelet domain using a best basis decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 415-427.
    13. Tong Liu & Xu Jin & Moran Wang, 2018. "Critical Resolution and Sample Size of Digital Rock Analysis for Unconventional Reservoirs," Energies, MDPI, vol. 11(7), pages 1-15, July.
    14. Bayani, Atiyeh & Alexander, Prasina & Azarnoush, Hamed & Rajagopal, Karthikeyan & Jafari, Sajad & Nazarimehr, Fahimeh, 2023. "Designing networks with specific synchronization transitions independent of the system’s dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    15. Mandzhieva, Radmila & Subhankulova, Rimma, 2021. "Practical aspects of absolute permeability finding for the lattice Boltzmann method and pore network modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    16. Salina Borello, Eloisa & Peter, Costanzo & Panini, Filippo & Viberti, Dario, 2022. "Application of A∗ algorithm for microstructure and transport properties characterization from 3D rock images," Energy, Elsevier, vol. 239(PC).
    17. Quispe, Laura V.C. & Tohalino, Jorge A.V. & Amancio, Diego R., 2021. "Using virtual edges to improve the discriminability of co-occurrence text networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    18. Maiorino, Enrico & Rizzi, Antonello & Sadeghian, Alireza & Giuliani, Alessandro, 2017. "Spectral reconstruction of protein contact networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 804-817.
    19. Tong Liu & Shiming Zhang & Moran Wang, 2021. "Does Rheology of Bingham Fluid Influence Upscaling of Flow through Tight Porous Media?," Energies, MDPI, vol. 14(3), pages 1-15, January.
    20. Romain Guibert & Marfa Nazarova & Marco Voltolini & Thibaud Beretta & Gerald Debenest & Patrice Creux, 2022. "Influence of Standard Image Processing of 3D X-ray Microscopy on Morphology, Topology and Effective Properties," Energies, MDPI, vol. 15(20), pages 1-14, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:416:y:2014:i:c:p:400-410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.