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Low Complexity near Lossless Image Compression Technique for Telemedicine

by Mohit Gupta, Narendra D Iondhe
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 29 - Number 7
Year of Publication: 2011
Authors: Mohit Gupta, Narendra D Iondhe
10.5120/3574-4931

Mohit Gupta, Narendra D Iondhe . Low Complexity near Lossless Image Compression Technique for Telemedicine. International Journal of Computer Applications. 29, 7 ( September 2011), 43-50. DOI=10.5120/3574-4931

@article{ 10.5120/3574-4931,
author = { Mohit Gupta, Narendra D Iondhe },
title = { Low Complexity near Lossless Image Compression Technique for Telemedicine },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 29 },
number = { 7 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume29/number7/3574-4931/ },
doi = { 10.5120/3574-4931 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:12.346729+05:30
%A Mohit Gupta
%A Narendra D Iondhe
%T Low Complexity near Lossless Image Compression Technique for Telemedicine
%J International Journal of Computer Applications
%@ 0975-8887
%V 29
%N 7
%P 43-50
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The minimizations of the storage space and transmission time are the two most important riding factors in image compression for telemedicine. Keeping this in view this paper intend to focus on a comparative investigation of three near lossless image compression technique, NLIC (near lossless image compression), SPIHT with DWT (Discrete Wavelets Transform), RLE (Run Length Encoding) with DCT (Discrete Cosine Transform). These techniques are analyzed and tested on various type of square state of art photographic images and medical images. The performance evaluation parameters like PSNR (Peak Signal to Noise Ratio), CR (Compression Ratio), RMSE (Root Mean Square Error), Computational time (CT) are calculated to evaluate the performance of mentioned near lossless image compression techniques.

References
  1. Al-Wahaib, M.S, KokSheik Wong (2010) ‘A Lossless Image Compression Algorithm Using Duplication Run Length Coding’, Proc IEEE Conference on Network Application Protocols and Services, pp. 245-250
  2. Avcibas, I, Memon N, Sankur, B, Sayood, K (2002), ”A progressive Lossless/Nearlossless imagecompression algorithm” IEEE Trans: Signal Processing, Vol 9, pp. 312 – 314,
  3. Avcibas, I. Memon, N., Sankur, B, Sayood, K (2005) ,’A Successively refinable lossless image-coding algorithm“ Proc IEEE Trans, Vol 53, PP. 445-452
  4. Bayer, F.M., Cintra, R.J (2010), Image Compression via a Fast DCT Approximation, IEEE Journals of Latin America Transactions, IEEE (Revista IEEE America Latina), Vol 8, pp. 708-713
  5. Bhooshan, S, Sharma, S. (2009) , An efficient and selective image compression schema using Huffman and adaptive interpolation, Inter. Conf. on Image and Vision Computing IVCNZ ’09, pp. 197 – 202.
  6. Carvajal, G., Penna, B., Magli, E (2008), Unified Lossy and Near-Lossless Hyper spectral Image Compression Based on JPEG 2000 , journals of IEEE Trans: Geosciences and Remote Sensing , Vol 5, pp. 593-597
  7. Chai, D, Bouzerdoum, A. (2001), JPEG2000 image compression: an overview , Intelligent Information Systems Conference, pp. 237 – 241.
  8. Chang-Hoon Son, Ji-Won Kim, Sung-Gun Song, Seong-Mo Park, Young-Min Kim (2010), Low complexity embedded compression algorithm for reduction of memory size and bandwidth requirements in the JPEG2000 encoder, journals of IEEE Trans: Consumer Electronics, Vol 56 pp. 2421-2429
  9. Chokchaitam, S., Iwahashi, M .”Lossless, near lossless and lossy adaptive coding based on lossless DCT “ Proc IEEE Conference on Circuit and System, Vol 1, pp. 781-784, 2002
  10. Chokchaitam, S.; Iwahashi, M.(2002) , Lossless, near lossless and lossy adaptive coding based on lossless DCT , Proc IEEE Conference on Circuit and System, Vol 1, pp. 781-784
  11. Chul Soo Lee, HyunWook Park (2003), Near-lossless/lossless compression of rror-diffused images using a two-pass approach , journals of IEEE Trans: Image Processing, Vol 12, pp. 170-175
  12. Gragory K. Wallace (1991), The JPEG Still Picture Compression Standard , Proc IEEE Trans on Consumer Electronics, Vol 38, pp. 18-34
  13. Howard, P. G., ‘Vitter, J.S. (1992) ,Parallel lossless image compression using Huffman and arithmetic coding, Proc. IEEE Data Compression Conf., pp. 299-308. Hu, Y. C., Chang, C.C. (2000) , A new lossless compression scheme based on Huffman coding scheme for image compression, Journal of Signal Processing: Image Communication, Vol. 16, No. 4, pp. 367-372.
  14. Lakhani, G(2003), ,Modified JPEG Huffman coding , journals of IEEE Trans: Image Processing, Vol 12, pp. 159-169
  15. M.A. Ansari , R.S. Anand (2008), Recent Trends in image compression and its application in telemedicine and teleconsultation. Proc National System Conferences, pp. 59-64
  16. Markos E, Papadonikolakis, E., Athanasios P, Kakarountas, E. (2008), Efficient high-performance implementation of JPEG-LS encoder, J. Real-Time Image Proc., Vol. 3, pp.303–310.
  17. Rane, S.D, Sapiro, G (2001) ‘Evaluation of JPEG-LS , the new lossless and controlled-lossy still image compression standard, for compression of high-resolution elevation data, journals of IEEE Trans: Geo Science and Remote Sensing, Vol 39, pp. 2298-2306
  18. Sabir, M.F, Sheikh, H.R, Heath, R.W, Jr, Bovik (2006) , A joint source-channel distortion model for JPEG compressed images’ journals of IEEE Trans: Image Processing, Vol 17, pp. 1349-1364
  19. Shaou-Gang Miaou, Fu-Sheng Ke, Shu-Ching Chen (2009), A Lossless Compression Method for Medical Image Sequences Using JPEG-LS and Interframe Coding, journals of IEEE Trans: Information Technology in Biomedicine Vol 13, pp. 818-821
  20. Suzuki, T., Ikehara, M. (2010) , Integer DCT Based on Direct-Lifting of DCT-IDCT for Lossless-to-Lossy Image Coding, IEEE Trans. Image Process., Vol.19, pp. 2958 – 2965.
  21. Taquet, J, Labit, C. (2010), Near-lossless and scalable compression for medical imaging using a new adaptive hierarchical oriented prediction, IEEE Conferences on Image Processing (ICIP), pp. 481-484.
  22. Thomas W. Fry and Scott A. Hauck (2005) ‘SPIHT Image Compression on FPGAs’ IEEE Trans. on circuits and systems for video technology, Vol. 15, pp. 1138-1147.
  23. Wei Haung, Shuai Chen and Gengsheng Zheng (2010),Improved Run Length Coding for Gray Level Images Using Gouraud Shading Method , Springer confrence on advance in Wireless Networks and Information System, Vol 72, pp. 19-26
  24. Weinberger, M. J., Sapiro, G., Seroussi, G. (2000) ,The LOCO-I lossless image compression algorithm: principle and standardization into JPEG-LS, IEEE Trans. Image Process., Vol. 9, pp. 1309–1324.
  25. Wen-ChienYen, Yen Yu chen (2005) ‘Natural Image Compression Based on Modified SPIHT ’ Proc. IEEE Conference on Annual ACIS International, pp. 100 – 104
  26. Wu, X., Memon, N. (2000) , Context-based lossless interband compression-extending CALIC, IEEE Trans. Image Process., Vol. 9, pp. 994 – 1001.
  27. Yang, M., Bourbakis, N. (2005) , An overview of lossless digital image compression techniques, Proc. IEEE Circuits and Systems 48th Midwest Symp., Vol. 2, 1099-1102.
Index Terms

Computer Science
Information Sciences

Keywords

Telemedicine SPIHT NLIC RLE DCT Huffman Coding

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