Browse > Article
http://dx.doi.org/10.6109/jkiice.2015.19.10.2403

An Orthogonal Approximate DCT for Fast Image Compression  

Kim, Seehyun (Department of Information and Communications Engineering, University of Suwon)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.10, 2015 , pp. 2403-2408 More about this Journal
Abstract
For image data the discrete cosine transform (DCT) has comparable energy compaction capability to Karhunen-Loeve transform (KLT) which is optimal. Hence DCT has been widely accepted in various image and video compression standard such as JPEG, MPEG-2, and MPEG-4. Recently some approximate DCT's have been reported, which can be computed much faster than the original DCT because their coefficients are either zero or the power of 2. Although the level of energy compaction is slightly degraded, the approximate DCT's can be utilized in real time implementation of image or visual compression applications. In this paper, an approximate 8-point DCT which contains 17 non-zero power-of-2 coefficients and high energy compaction capability comparable to DCT is proposed. Transform coding experiments with several images show that the proposed transform outperforms the published works.
Keywords
Approximate DCT; Energy compaction; High speed implementation; Orthogonality of transforms;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. J. Cintra, F. M. Bayer and C. J. Tablada, “Low complexity 8-point DCT approximation based on integer functions,” Signal Processing, 99, pp. 201-214, 2014.   DOI
2 S. Kim and W. Sung, “Fixed-point error analysis and word length optimization of 8x8 IDCT architectures,” IEEE Trans., Circuits and Systems for Video Technology, vol. 8, no. 8, pp. 935-940, Dec., 1998.   DOI
3 Haweel T. I., “A new square wave transform based on the DCT,” Signal Processing, 81, pp. 2309-2319, 2001.   DOI
4 R. K. Senapati, U. C. Pati, and K. K. Mahapatra, “A low complexity orthogonal 8x8 transform matrix for fast image compression,” Proc. Annual IEEE India Conference, pp. 1-4, 2014.
5 N. Brahimi and S. Bouguezel, “An efficient fast integer DCT transform for image compression with 16 addtions only,” Proc. IEEE 7th International Workshop on systems, signal Processing and Their Applications, pp. 71-74, 2011.
6 R. J. Cintra and F. M. Bayer, “A DCT approximation for image compression,” IEEE Signal Processing Letters, vol 18, no. 10, pp. 579-581, Oct. 2011.   DOI
7 K. Saraswathy, D. Vaithiyanathan and R. Seshasayanan, “A DCT approximation with low complexity for image compression,” IEEE International Conference on Communication and Signal Processing, pp. 464-468, Apr., 2013.
8 W. Pratt, Digital Image Processing, 4th Ed., Wiley-Interscience, 2007.
9 W. H. Chen, C. H. Smith, and S. C. Fralick, “A fast computational algorithm for the discrete cosine transform,” IEEE Trans. Comm., vol. 25, no. 9, pp. 1004-1009, Sep., 1977.   DOI
10 B. G. Lee, “A new algorithm to compute the discrete cosine transform,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 32, no. 12, pp. 1234-1245, Dec., 1984.