Efficient Image Compression Algorithm Using Modified IWT and SPIHT for CMOS Image Sensor

(*) Corresponding author

Authors' affiliations

DOI's assignment:
the author of the article can submit here a request for assignment of a DOI number to this resource!
Cost of the service: euros 10,00 (for a DOI)


Image retargeting is a vital requirement for the CMOS image sensor based applications at the user end. Many of the existing techniques are basically content based image retargeting which has high computational complexity and is not suitable for CMOS image sensors. For avoiding this practical hurdles, we addresses the increasing demand of visual signal delivery to terminals with arbitrary resolutions without heavy computational burden to the receiving end by incorporating the principle of seam carving  into a wavelet codec. For each input image, block-based seam energy map is generated in the pixel domain and the integer wavelet transform is performed on the retargeted image. Unlike the conventional wavelet-based coding schemes, IWT coefficients are grouped and encoded according to the resultant seam energy map and bit streams are transmitted in energy descending order. In decoder, the end user has the ultimate choice for the spatial scalability without the need to examine the visual content and the image with arbitrary aspect ratio can be reconstructed.
Copyright © 2013 Praise Worthy Prize - All rights reserved.


Integer Wavelet Transform; Reverse Lifting; Seam Carving; SPIHT

Full Text:



M.A. Ansari, R.S. Anand, Recent trends in image compression and its application in telemedicine and teleconsultation, Xxxii National Systems Conference, Nsc 2008, December 17-19, 2008.

Debin Zhao, Y. K. Chan, and Wen GAO, Low-Complexity and Low- Memory Entropy Coder For Image Compression, IEEE Transactions On Circuits And Systems For Video Technology, Vol. 11, No. 10, October 2001.

Ahmed Abu- Hajar and Ravi Sankar, Region of interest coding using partial-spiht, IEEE International Conference on Acoustics, Speech and Signal processing , May 2004.

D. Vijendra Babu, Dr.N.R.Alamelu, Wavelet Based Medical Image Compression using Roi Ezw, International Journal Of Recent Trends In Engineering, Vol 1, No. 3, May 2009.

N. T. N. Anh, W. X. Yang, and J. F.Cai, Seam carving extension: A compression perspective, ACM Conference on Multimedia, pp. 825–828, Oct. 2009.

Villegas, O.O.V. Elias, R.P. Rayon Villela, Patricia, Magadan Salazar, and Andrea, Edge Preserving Lossy Image Compression with Wavelets and Contourlets, Latin America Transactions IEEE, Vol. 5, No. 2, May 2007.

Abu-Hajar, Sankar, Ravi , Enhanced partial-SPIHT for lossless and lossy image compression, IEEE International conference on Acoustics, Speech and Signal processing , Vol. 3, pp. 253-256, April 2003.

Milin Zhang, Amine Bermak, Quadrant-based Online Spatial and Temporal Compressive Acquisition for CMOS Image Sensor, IEEE Transactions on Very Large Scale Integration Systems, Vol. 19, No. 9, September 2011.

9. W. Bellil, C. Ben Amar, A. M. Alimi, Multi Library Wavelet Neural Network for Lossless Image Compression, (2007) International Review on Computers and Software (IRECOS), 2 (5), pp. 520-526.

A. Ouled Zaid, A. Makhloufi, A. Bouallegue, C. Olivier, A. Nait-Ali, Blind Watermarking Integrated to Wavelet Image Coding Scheme, (2008) International Review on Computers and Software (IRECOS), 3 (1), pp. 53-61.

Salija.P, Manimekalai.M.A.P and N.A. Vasanthi, ROI and Seam-SPIHT based Efficient Image Compression for Mobile Multimedia and Medical Applications, International Journal of Computer Applications, Volume 64– No.12, February 2013.

Yuichi Tanaka, Madoka Hasegawa and Shigeo Kato, Improved image concentration for artifact-free image dilution and its application to image coding, International conference on Image Processing, IEEE , pg. no 1225-1228, September 2010.

Pardo, M.B., Rey Juan Carlos, Embedded Lossy Image Compression based on Wavelet transform, 4 th EURASIP – IEEE region 8 international Symposium on Video/Image Processing and Multimedia Communications, pages 195-199, May 2002.

Hai Wang, Fast Image Fractal Compression with Graph-Based Image Segmentation Algorithm, International Journal of Graphics, Vol. 1, No.1, November, 2010.

Rammohan, T., Sankaranarayanan, K., Vijayakumari, V., An efficient image compression technique with dead zone quantization through wavelet-based contourlet transform with Modified SPIHT encoding, (2013) International Review on Computers and Software (IRECOS), 8 (6), pp. 1313-1320.

Vasanthi Kumari, P., Thanushkodi, K., A secure fast 2D-discrete fractional Fourier transform based medical image compression using SPIHT algorithm with Huffman encoder, (2013) International Review on Computers and Software (IRECOS), 8 (7), pp. 1702-1710.

Cyriac, M., Chellamuthu, C., A wavelet based approach for near-lossless image compression using logarithmic transformation, (2013) International Review on Computers and Software (IRECOS), 8 (6), pp. 1334-1340.


  • There are currently no refbacks.

Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize