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Pyramid based Progressive Transmission System with Hybrid Compression Scheme for Medical Images

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Abstract

Transmission of medical images over the internet has become common in telemedicine services. Telemedicine is an enabler for rural health care services where network quality varies over time and there is a need for robustness in presence of poor network quality and efficient use of bandwidth. At the same time, the quality of medical images cannot be compromised with network constraints. In this work, a progressive transmission system with an efficient compression scheme is proposed for the effectual transmission of medical images over the internet with consideration for optimal use of network bandwidth. The image quality can be fine-tuned based on network bandwidth availability and user requirements.

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References

  1. Szoke Ildiko-Angelica, Diana Lungeanu, Stefan Holban, “Image Compression Techniques Using Local Binary Pattern.” In 2015 IEEE 13th International Symposium on Applied Machine Intelligence and Informatics (SAMI), pp. 139–143. IEEE, 2015.

  2. Kumar S, Paul TU, Raychoudhury A. Image compression using approximate matching and run length. Internat J Adv Comput Sci Appl. 2011;2:6.

    Google Scholar 

  3. Zhu H, Zhao C, Zhang X. A novel image encryption-compression scheme using hyper-chaos and Chinese remainder theorem. Signal Proc Image Commun. 2013;28(6):670–80.

    Article  Google Scholar 

  4. Yuen CH, Wong KW. A chaos-based joint image compression and encryption scheme using DCT and SHA-1. Applied Soft Computing. 2011;11(8):5092–8.

    Article  Google Scholar 

  5. Jin Li, Xing F, Sun T, You Z. Multispectral image compression based on DSC combined with CCSDS-IDC. Scient World J. 2014;6:12–34.

    Google Scholar 

  6. Bayazit U. Adaptive spectral transform for wavelet-based color image compression. IEEE Trans Circuits Syst Video Technol. 2011;21(7):983–92.

    Article  Google Scholar 

  7. Taquet J, Labit C. Hierarchical oriented predictions for resolution scalable lossless and near-lossless compression of CT and MRI biomedical images. IEEE Trans Image Process. 2012;21(5):2641–52.

    Article  MathSciNet  Google Scholar 

  8. Hurtik Petr, Irina Perfilieva. A hybrid image compression algorithm based on jpeg and fuzzy transform. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1–6. IEEE, 2017.

  9. Di Martino F, Loia V, Perfilieva I, Sessa S. An image coding/decoding method based on direct and inverse fuzzy transforms. Int J Approx Rea. 2008;48(1):110–31.

    Article  Google Scholar 

  10. Jiang H, Ma Z, Yang Hu, Yang B, Zhang L. Medical image compression based on vector quantization with variable block sizes in wavelet domain. Comput Intell Neurosci. 2012;8:4.

    Google Scholar 

  11. Alshehri SA. Neural network technique for image compression. IET Image Proc. 2016;10(3):222–6.

    Article  Google Scholar 

  12. Archana JN. Progressive transmission techniques in medical imaging. Internat J Multidisci Curr Res. 2013;1(74–80):2013.

    Google Scholar 

  13. Xu BH, Hao YS. Research on image technology with progressive image compression based on JPEG and Laplacian pyramid. Adv Mater Res. 2014;886:650–4.

    Article  Google Scholar 

  14. Dridi M, Hajjaji MA, Bouallegue B, Mtibaa A. An enhancement medical image compression algorithm based on neural network. Internat J Adv Computer Sci Appl. 2016;7(5):484–9.

    Google Scholar 

  15. Patel R, Kumar V, Tyagi V, Asthana V. A fast and improved Image compression technique using Huffman coding. Internat Conf Wirless Commun Signal Proc Netw. 2016;2:2283–6.

    Google Scholar 

  16. Ravikiran HK, Paramesha D. Performance analysis of biorthogonal wavelet and SPHIT for progressive image transmission and reconstruction. Internat J Emerging Technol Innov Res. 2018;5(1):723–5.

    Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the support and contribution of Management and Principal of Rajeev Institute of Technology, Hassan and GSSS Institute of Engineering and Technology for Women, Mysuru.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Rajeev Institute of Technology, Affiliated to Visvesvaraya Technological University, Hassan, 573201, India

    H. K. Ravikiran

  2. Department of E&C Engineering, Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Affiliated to Visvesvaraya Technological University, Mysuru, 570016, India

    J. Jayanth

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  1. H. K. Ravikiran
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  2. J. Jayanth
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Correspondence to H. K. Ravikiran.

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The work is not funded by any agency and the authors declare that they have no conflict of interest.

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This article is part of the topical collection “Data Science and Communication” guest-edited by Kamesh Namudri, Naveen Chilamkurti, Sushma S J and S. Padmashree.

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Ravikiran, H.K., Jayanth, J. Pyramid based Progressive Transmission System with Hybrid Compression Scheme for Medical Images. SN COMPUT. SCI. 2, 155 (2021). https://doi.org/10.1007/s42979-021-00534-7

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  • DOI: https://doi.org/10.1007/s42979-021-00534-7

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