A Novel VLSI Architecture of Hybrid Image Compression Model based on Reversible Blockade Transform
Image compression can improve the performance of
the digital systems by reducing time and cost in image storage
and transmission without significant reduction of the image quality.
Furthermore, the discrete cosine transform has emerged as the new
state-of-the art standard for image compression. In this paper, a
hybrid image compression technique based on reversible blockade
transform coding is proposed. The technique, implemented over
regions of interest (ROIs), is based on selection of the coefficients
that belong to different transforms, depending on the coefficients is
proposed. This method allows: (1) codification of multiple kernals
at various degrees of interest, (2) arbitrary shaped spectrum,and (3)
flexible adjustment of the compression quality of the image and the
background. No standard modification for JPEG2000 decoder was
required. The method was applied over different types of images.
Results show a better performance for the selected regions, when
image coding methods were employed for the whole set of images.
We believe that this method is an excellent tool for future image
compression research, mainly on images where image coding can
be of interest, such as the medical imaging modalities and several
multimedia applications. Finally VLSI implementation of proposed
method is shown. It is also shown that the kernal of Hartley and
Cosine transform gives the better performance than any other model.
[1] Abbas Razavi, Rutie Adar, Issac Shenberg, "VLSI Implementation of
an Image Compression Algorithm with a New Rate Control Capability"
IEEE International Conference on Multimedia, Aug 1992, CA, USA,
pp. V.669- V.672
[2] Jie Guo; Cheng-ke Wu; Yun-song Li; Ke-yan Wang; Song, J."Memoryefficient
architecture including DWT and EC for JPEG2000" 9th International
Conference on Solid-State and Integrated-Circuit Technology,
2008. 20-23 Oct. 2008. pp. 2192-2195.
[3] Pellegri, P.; Novati, G.; Schettini, R., "Multispectral loss-less compression
using approximation methods" in Proceedings of IEEE International
Conference on Image Processing (ICIP), Volume 2, pp. 638-641,
September 2005.
[4] Karp R, "Minimum-redundancy coding for the discrete noiseless channel",
in Proceedings of IEEE Transactions on Information Theory,
Volume 7, Issue 1, pp. 27-38, January 1961.
[5] Ziv, J., and A. Lempel, "A Universal Algorithm for Sequential Data
Compression," in Proeedings of IEEE Transactions on Information
Theory", vol. 23, no. 3, pp. 337-343, October, 1977.
[6] Allott, D., Clarke, R.J., "Shape adaptive activity controlled multistage
gain shape vector quantisation of images", in Proceedings of IET
Electronics Letters, Volume 21, Issue 9, April 25, 1985.
[7] Yibin Yang; Boroczky, L.; "A new enhancement method for digital
video applications" in Proceedings of IEEE Transactions on Consumer
Electronics, Volume 48, Issue 3, pp. 435-443, August 2002.
[8] Giancarlo, R. and Grossi, R. "On the construction of classes of suffix
trees for square matrices: algorithms and applications"In Proceedings of
ICALP. 1995.
[9] T. Fukushima, "A survey of image processing LSIs in Japan," IEEE 10th
Int. Conf on Patt. Recog., Atlantic City, NJ, pp. 394-401, June 1990.
[10] K. Gaedke, H. Jeschke, and P. Pirsch, "A VLSI-based MIMD architecture
of a multiprocessor system for real-time video processing
applications," J. VLSI Signal Proc., vol. 5, pp. 159-169, Apr. 1993.
[11] W. Gehrke, R. Hoffer, and P. Pirsch, "A hierarchical multiprocessor
architecture based on heterogeneous processors for video coding applications,"
Proc. ICASSP -94, vol. 2, IEEE Press 1994.
[12] J. Goto et al., "250-MHz BiCMOS super-high-speed video signal
processor (S-VSP) ULSI," IEEE J. Solid-state Circ., vol. 26, no. 12,
pp. 1876-1884, 1991.
[13] Komatsu, K.; Sezaki, K. "Reversible discrete cosine transform" International
Conference on Acoustics, Speech and Signal Processing, 1998,
Volume 3, 12-15 May 1998 pp.1769 - 1772.
[14] Lei Wang; Jiaji Wu; Licheng Jiao; Li Zhang; Guangming Shi, "Lossy
to lossless image compression based on reversible integer DCT" 15th
International Conference on Image Processing, 2008, 12-15 Oct. 2008
pp.1037 - 1040.
[15] Soo-Chang Pei; Jian-Jiun Ding, "Reversible Integer Color Transform"
IEEE Transactions on Image Processing, Volume 16, Issue 6, June 2007,
pp.1686 - 1691.
[16] A. G. Weber, "The USC-SIPI Image Database. Version 5," USCSIPI
Rep #315, Oct 1997 http://sipi.usc.edu/service/database/Database.htm.
[17] http://www.vlsitechnology.org/
[18] Ziping Hu; Verma, P.; Sluss, J. "Routing in Degree-Constrained FSO
Mesh Networks" International Conference Future Generation Communication
and Networking, 2008. Volume 1, 13-15 Dec. 2008 pp.208 -
215
[1] Abbas Razavi, Rutie Adar, Issac Shenberg, "VLSI Implementation of
an Image Compression Algorithm with a New Rate Control Capability"
IEEE International Conference on Multimedia, Aug 1992, CA, USA,
pp. V.669- V.672
[2] Jie Guo; Cheng-ke Wu; Yun-song Li; Ke-yan Wang; Song, J."Memoryefficient
architecture including DWT and EC for JPEG2000" 9th International
Conference on Solid-State and Integrated-Circuit Technology,
2008. 20-23 Oct. 2008. pp. 2192-2195.
[3] Pellegri, P.; Novati, G.; Schettini, R., "Multispectral loss-less compression
using approximation methods" in Proceedings of IEEE International
Conference on Image Processing (ICIP), Volume 2, pp. 638-641,
September 2005.
[4] Karp R, "Minimum-redundancy coding for the discrete noiseless channel",
in Proceedings of IEEE Transactions on Information Theory,
Volume 7, Issue 1, pp. 27-38, January 1961.
[5] Ziv, J., and A. Lempel, "A Universal Algorithm for Sequential Data
Compression," in Proeedings of IEEE Transactions on Information
Theory", vol. 23, no. 3, pp. 337-343, October, 1977.
[6] Allott, D., Clarke, R.J., "Shape adaptive activity controlled multistage
gain shape vector quantisation of images", in Proceedings of IET
Electronics Letters, Volume 21, Issue 9, April 25, 1985.
[7] Yibin Yang; Boroczky, L.; "A new enhancement method for digital
video applications" in Proceedings of IEEE Transactions on Consumer
Electronics, Volume 48, Issue 3, pp. 435-443, August 2002.
[8] Giancarlo, R. and Grossi, R. "On the construction of classes of suffix
trees for square matrices: algorithms and applications"In Proceedings of
ICALP. 1995.
[9] T. Fukushima, "A survey of image processing LSIs in Japan," IEEE 10th
Int. Conf on Patt. Recog., Atlantic City, NJ, pp. 394-401, June 1990.
[10] K. Gaedke, H. Jeschke, and P. Pirsch, "A VLSI-based MIMD architecture
of a multiprocessor system for real-time video processing
applications," J. VLSI Signal Proc., vol. 5, pp. 159-169, Apr. 1993.
[11] W. Gehrke, R. Hoffer, and P. Pirsch, "A hierarchical multiprocessor
architecture based on heterogeneous processors for video coding applications,"
Proc. ICASSP -94, vol. 2, IEEE Press 1994.
[12] J. Goto et al., "250-MHz BiCMOS super-high-speed video signal
processor (S-VSP) ULSI," IEEE J. Solid-state Circ., vol. 26, no. 12,
pp. 1876-1884, 1991.
[13] Komatsu, K.; Sezaki, K. "Reversible discrete cosine transform" International
Conference on Acoustics, Speech and Signal Processing, 1998,
Volume 3, 12-15 May 1998 pp.1769 - 1772.
[14] Lei Wang; Jiaji Wu; Licheng Jiao; Li Zhang; Guangming Shi, "Lossy
to lossless image compression based on reversible integer DCT" 15th
International Conference on Image Processing, 2008, 12-15 Oct. 2008
pp.1037 - 1040.
[15] Soo-Chang Pei; Jian-Jiun Ding, "Reversible Integer Color Transform"
IEEE Transactions on Image Processing, Volume 16, Issue 6, June 2007,
pp.1686 - 1691.
[16] A. G. Weber, "The USC-SIPI Image Database. Version 5," USCSIPI
Rep #315, Oct 1997 http://sipi.usc.edu/service/database/Database.htm.
[17] http://www.vlsitechnology.org/
[18] Ziping Hu; Verma, P.; Sluss, J. "Routing in Degree-Constrained FSO
Mesh Networks" International Conference Future Generation Communication
and Networking, 2008. Volume 1, 13-15 Dec. 2008 pp.208 -
215
@article{"International Journal of Electrical, Electronic and Communication Sciences:64092", author = "C. Hemasundara Rao and M. Madhavi Latha", title = "A Novel VLSI Architecture of Hybrid Image Compression Model based on Reversible Blockade Transform", abstract = "Image compression can improve the performance of
the digital systems by reducing time and cost in image storage
and transmission without significant reduction of the image quality.
Furthermore, the discrete cosine transform has emerged as the new
state-of-the art standard for image compression. In this paper, a
hybrid image compression technique based on reversible blockade
transform coding is proposed. The technique, implemented over
regions of interest (ROIs), is based on selection of the coefficients
that belong to different transforms, depending on the coefficients is
proposed. This method allows: (1) codification of multiple kernals
at various degrees of interest, (2) arbitrary shaped spectrum,and (3)
flexible adjustment of the compression quality of the image and the
background. No standard modification for JPEG2000 decoder was
required. The method was applied over different types of images.
Results show a better performance for the selected regions, when
image coding methods were employed for the whole set of images.
We believe that this method is an excellent tool for future image
compression research, mainly on images where image coding can
be of interest, such as the medical imaging modalities and several
multimedia applications. Finally VLSI implementation of proposed
method is shown. It is also shown that the kernal of Hartley and
Cosine transform gives the better performance than any other model.", keywords = "VLSI, Discrete Cosine Transform, JPEG, Hartleytransform, Radon Transform", volume = "3", number = "4", pages = "1048-7", }