Embedded DCT-based still image coding algorithm

Image analysis – Image compression or coding – Shape – icon – or feature-based compression

Reexamination Certificate

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C382S240000, C382S248000

Reexamination Certificate

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07085425

ABSTRACT:
In an embedded DCT-based (EDCT) image coding method, decoded images which give better PSNR over earlier JPEG and DCT-based coders are obtained by a scanning order starting, for each bitplane, from the upper left corner of a DCT block (corresponding to the DC coefficient) and transmitting the coefficients in an order of importance. An embedded bit-stream is produced by the encoder. The decoder can cut the bit-stream at any point and therefore reconstruct an image at a lower bitrate. The quality of the reconstructed image at this lower rate is the same as if the image was coder directly at that rate. Near lossless reconstruction of the image is possible, up to the accuracy of the DCT coefficients. The algorithm is very useful in various applications, like WWW, fast browsing of databases, medical imaging, etc.

REFERENCES:
patent: 4698689 (1987-10-01), Tzou
patent: 4903317 (1990-02-01), Nishihara et al.
patent: 5001561 (1991-03-01), Haskell et al.
patent: 5196933 (1993-03-01), Henot
patent: 5333212 (1994-07-01), Ligtenberg
patent: 5339108 (1994-08-01), Coleman et al.
patent: 5363138 (1994-11-01), Hayashi et al.
patent: 5563960 (1996-10-01), Shapiro
patent: 5757974 (1998-05-01), Impagliazzo et al.
patent: 5901249 (1999-05-01), Ito et al.
patent: 5991816 (1999-11-01), Percival et al.
patent: 6804405 (2004-10-01), Christopoulos et al.
patent: 2002/0126906 (2002-09-01), Christopoulos et al.
Xion et al., “A DCT-based embedded image coder”, IEEE Signal Processing Letters, vol. 3 issue: 11, Nov. 1996, pp. 289-290.
Nguyen-Phi et al., “DWT image compression using contextual bitplane coding of wavelet coefficients”. Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on, vol. 4, Apr. 21-24, 1997, pp. 2969-2972.
Laurance et al. “Embedded DCT coding with significance masking”, Acoustics, Speech, and Signal Processing, 1997. ICASSP 97., 1997 IEEE International Conference on, vol. 4, Apr. 21-24, 1997, pp. 2717-2720.
Atsumi et al. “Lossy/Lossless Region-of-Interest Image Coding Based on Set Partitioning in Hierarachical trees”, ISO/IEC JTC 1/SC 29/WG 1 N839. Mar. 23, 1998.
Panagiotidis et al, “Region-of-Interest Based Compression of Magnetic Resonance Imaging Data”, Proceedings/IWISP '96, Third International Workshop on Image and Signal Processing on the Theme of advances in Computational Intelligence, Edited by Mertzios et al, Nov. 4-7, 1996, pp. 31-35.
Proceedings of the SPIE Conference on Visual Communications and Image Processing, vol. 2094 Part 2, 1993, A Said et al., “Reversible image compression via multiresolution representation and predictive coding”, pp. 664-674.
Signal Processing, vol. 59, No. 2, Jun. 1997, J. Ström et al., “Medical image compression with lossless regions of interest”, pp. 155-171.
International Search Report PCT/SE98/01809.
U.S. Appl. No. 09/532,768, filed Mar. 22, 2000 entitled “Lossless Region of Internet Coding”.
Heer et al, “A Comparison of Reversible Methods for Data Compression”, SPIE vol. 1233 Medical Imaging IV; Image Processing (1990), pp. 354-365.
Viahakis et al. “ROI Approach To Wavelet-Based, Hybrid Compression Of MR Images”, Image Processing and Its Applications, 1997, Sixth International Conference, vol. 2, Jul. 14-17, 1997, pp. 833-837.
A New, Fast, and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees, Said et al., IEEE Transactions on Circuits and System for Video Technology, vol. 6, No. 3, Jun. 1996, pp. 243-250.
Lossy/lossless Region-of-Internet Image Coding Based on Set Partitioning in Hierarchical Tress, Atsumi et al., Proceedings of 1998 International Conference on Image Processing ICIP 98, vol. 1, Oct. 4-7, 1998, pp. 87-91.

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