A Comparative Study of Image Compression Algorithms

Download Full Text
Author(s):
Kiran Bindu, Anita Ganpati, Aman Kumar Sharma
Published Date:
September 05, 2012
Issue:
Volume 2, Issue 5
Page(s):
37 - 42
DOI:
10.7815/ijorcs.25.2012.046
Views:
6321
Downloads:
702

Keywords:
compression, dct, dwt, hybrid, image compression.
Citation:
Kiran Bindu, Anita Ganpati, Aman Kumar Sharma, "A Comparative Study of Image Compression Algorithms". International Journal of Research in Computer Science, 2 (5): pp. 37-42, September 2012. doi:10.7815/ijorcs.25.2012.046 Other Formats

Abstract

Digital images in their uncompressed form require an enormous amount of storage capacity. Such uncompressed data needs large transmission bandwidth for the transmission over the network. Discrete Cosine Transform (DCT) is one of the widely used image compression method and the Discrete Wavelet Transform (DWT) provides substantial improvements in the quality of picture because of multi resolution nature. Image compression reduces the storage space of image and also maintains the quality information of the image. In this research study the performance of three most widely used techniques namely DCT, DWT and Hybrid DCT-DWT are discussed for image compression and their performance is evaluated in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Compression Ratio (CR). The experimental results obtained from the study shows that the Hybrid DCT- DWT technique for image compression has in general a better performance than individual DCT or DWT.

  1. Anil Kumar Katharotiya, Swati Patel, Mahesh Goyani, “Comparative Analysis between DCT & DWT Techniques of Image Compression”. Journal of Information Engineering and Applications, Vol. 1, No. 2, 2011.
  2. R. K. Rao, P. Yip, “Discrete Cosine Transform: Algorithms, Advantages and Applications”. NY: Academic, 1990.
  3. G. Joy, Z. Xiang, “Reducing false contours in quantized color images”. Computer and Graphics, Elsevier, Vol. 20, No. 2, 1996 pp: 231–242. doi: doi:10.1016/0097-8493(95)00098-4
  4. T.-H. Yu, S. K. Mitra, “Wavelet based hybrid image coding scheme”. Proc. IEEE Int Circuits and Systems Symp, Vol. 1, 1997, pp: 377–380. doi: 10.1109/ISCAS.1997.608746
  5. U. S. Mohammed, W. M. Abd-elhafiez, “Image coding scheme based on object extraction and hybrid transformation technique”. International Journal of Engineering Science and Technology, Vol. 2, No. 5, 2010, pp: 1375–1383.
  6. R. Singh, V. Kumar, H. K. Verma, “DWT-DCT hybrid scheme for medical image compression”. Journal of Medical Engineering and Technology, Vol. 31, No. 2, 2007, pp: 109–122. doi: 10.1080/03091900500412650
  7. R. K. Rao, P. Yip, “Discrete Cosine Transform: Algorithms, Advantages and Applications”. NY: Academic, 1990.
  8. Suchitra Shrestha, “Hybrid DWT-DCT Algorithm for Image and Video Compression applications”, A Thesis, University of Saskatchewan, Electrical and Computer Engineering Dept., Canada, 2010. doi: 10.1109/ISSPA.2010.5605474
  9. K. A. Wahid, M. A. Islam, S. S. Shimu, M. H. Lee, S. Ko, “Hybrid architecture and VLSI implementation of the Cosine-Fourier-Haar transforms”. Circuits, Systems and Signal Processing, Vol. 29, No. 6, 2010, pp: 1193–1205.
  10. Suchitra Shrestha Khan Wahid (2010). “Hybrid DWT-DCT Algorithm for Biomedical Image and Video Compression Applications”. Proceeding 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).
  11. Swastik Das and Rasmi Ranjan Sethy, “Digital Image Compression using Discrete Cosine Transform and Discrete Wavelet Transform”, B.Tech. Dissertation, NIT, Rourkela, 2009.
  12. Rupinder Kaur, Nisha Kaushal, “Comparative Analysis of various Compression Methods for Medical Images”. National Institute of Technical Teachers’ Training and Research, Panjab University Chandigarh.
  13. Rehna V.J, Jeya Kumar M.K, “Hybrid Approach to Image Coding: A Review”. International Journal of Advanced Computer Science and Applications, Vol. 2, No. 7, 2011.

  • Mulla, Afshan, Namrata Gunjikar, and Radhika Naik. "Comparison of Different Image Compression Techniques." International Journal of Computer Applications 70.28 (2013).
  • Bansal, Nikita. "Image Compression Using Hybrid Transform Technique." Journal of Global Research in Computer Science 4.1 (2013): 13-17.
  • Sekaran, KC Chandra, and K. Kuppusamy. "Efficiency of Gaussian Pyramid Compression Technique for Biometric Images." International Journal of Computer Science Issues (IJCSI) 11.3 (2014): 77.
  • Ranparia, Mital, and Falgun Thakkar. "Wavelet based Abnormality Detection and Compression of MRI Images", International Journal of Emerging Trends in Electrical and Electronics (IJETEE), pp.61-65, Vol. 1, Issue. 2, March-2013.
  • Moorthi, M., and R. Amutha. "An Integrated Model for Compression of Medical Images in Telemedicine." (2014).
  • PHYO, EIEI, and Nang Aye Aye Htwe. "JPEG Image Compression and Decompression using Discrete Cosine Transform (DCT)", International Journal of Scientific Engineering and Technology Research, pp.1780-1785, Vol. 3, Issue 9, May 2014.
  • Khatri, Pooja, and Rajiv Dahiya. "COMPARATIVE STUDY OF DCT, DWT & HYBRID (DCT-DWT) TRANSFORM USING N LEVEL OF DECOMPOSITION", International Journal For Technological Research In Engineering, pp.2190-2193, Vol.2, Issue 9, May 2015.
  • Kowalik-Urbaniak, Ilona Anna. The quest for “diagnostically lossless” medical image compression using objective image quality measures. Diss. University of Waterloo, 2014.
  • Jangir, Jitendra, et al. "Study and Analysis of Image Compression Techniques For Enhancement of Compression Ratio For Efficient Transmission." (2014).
  • Sekaran, KC Chandra, and K. Kuppusamy. "Performance Analysis of Compression Techniques Using SVD, BTC, DCT and GP", IOSR Journal of Computer Engineering(IOSR-JCE), pp.6-11, Vol.17, Issue 1, Jan-Feb 2015.