Abstract
A novel lossless colour image compression scheme based on a reversible colour transform (RCT) and Burrows–Wheeler compression algorithm (BWCA) is presented. The lossless transformation from RGB to YUV colour space provides highly correlated pixel intensities in the transformed image, thus aiding in higher compression. The proposed scheme uses a two-pass Burrows–Wheeler transform (BWT) for the individual source image colour planes to enhance grey-level homogeneity in the 2-D space. Compression efficiency is compared against various schemes including the JPEG 2000 lossless compression scheme and the previously developed kernel move-to-front transform-based BWCA (kernel BWCA). Validation is carried out via small- and large-size images. The proposed method using RCT with bi-level BWT results in better compression by taking advantage of the redundancy in the grey levels brought by the YUV colour space. For small-size images, it achieves 45 and 126 per cent more compression than the JPEG2000 lossless and kernel BWCA scheme, respectively. Among the different schemes compared, the proposed scheme achieves overall best performance and is well suited to small- and large-size image data compression.
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References
Ouni, T., Lassoued, A., Abid, M.: Lossless image compression using gradient based space filling curves (G-SFC). Signal Image Video Process. 9(2), 277–293 (2015)
Anusuya, V., Raghavan, V.S., Kavitha, G.: Lossless compression on MRI images using SWT. J. Digit. Imaging 27(5), 594–600 (2014)
Srinivasan, K., Dauwels, J., Reddy, M.R.: A two-dimensional approach for lossless EEG compression. Biomed. Signal Process. Control 6(4), 387–394 (2011)
Mao, Q., et al.: Efficient and lossless compression of raster maps. Signal Image Video Process. 9(1), 133–145 (2015)
Sun, W., et al.: High performance reversible data hiding for block truncation coding compressed images. Signal Image Video Process. 7(2), 297–306 (2013)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, vol. 2. Prentice-Hall Inc, New Jersey (2002)
Skodras, A., Christopoulos, C., Ebrahimi, T.: The Jpeg 2000 still image compression standard. IEEE Signal Process. Mag. 18(5), 36–58 (2001)
Ponomarenko, N.N., et al.: Adaptive visually lossless JPEG-based color image compression. Signal Image Video Process. 7(3), 437–452 (2013)
Zamora, G., Mitra, S.: Lossless coding of color images using color space transformations. In: 11th IEEE Symposium on Computer-Based Medical Systems, Proceedings, pp. 13–18, IEEE Computer Society, Los Alamitos (1998)
Colantoni, P., Al.: Color space transformations, (2004)
de Queiroz, R.L.: On independent color space transformations for the compression of CMYK images. IEEE Trans. Image Process. 8(10), 1446–1451 (1999)
Chou, C.H., Liu, K.C.: Colour image compression based on the measure of just noticeable colour difference. IET Image Process. 2(6), 304–322 (2008)
Tiwari, A.K., Kumar, R.V.R.: A minimum entropy based switched adaptive predictor for lossless compression of images. Signal Image Video Process. 3(4), 307–318 (2009)
Gormish, M.J., et al.: Lossless and nearly lossless compression for high quality images. In: Algazi, V.R., Ono, S., Tescher, A.G. (eds.) SPIE: Very High Resolution and Quality Imaging II, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), pp. 62–70. Spie-Int Soc Optical Engineering, Bellingham (1997)
Przelaskowski, A.: Effective integer-to-integer transforms for JPEG2000 coder. In: Laine, A.F., Unser, M.A., Aldroubi, A. (eds.) Wavelets: Applications in Signal and Image Processing IX, Proceedings of the Society of Photo-Optical Instrumentation Engineers (Spie), pp. 299–310. Spie-Int Soc Optical Engineering, Bellingham (2001)
Rabbani, M., Joshi, R.: An overview of the jpeg 2000 still image compression standard. Signal Process. Image Commun. 17(1), 3–48 (2002)
Chen, Y., Hao, P.: Integer reversible transformation to make JPEG lossless. In: 2004 7th International Conference on Signal Processing Proceedings, vol 1–3, pp. 835–838, Publishing House Electronics Industry, Beijing (2004)
Burrows, M., Wheeler, D.J.: A block-sorting lossless data compression algorithm. SRC Research Report 124. Digital Systems Research Center, Palo Alto (1994)
Bell, T.C., Cleary, J.G., Witten, I.H.: Text Compression. Prentice-Hall, New Jersey (1990)
Abel, J.: Incremental frequency count—a post BWT-stage for the Burrows–Wheeler compression algorithm. Softw. Pract. Exp. 37(3), 247–265 (2007)
Abel, J.: Post BWT stages of the Burrows–Wheeler compression algorithm. Softw. Pract. Exp. 40(9), 751–777 (2010)
Deorowicz, S.: Improvements to Burrows–Wheeler compression algorithm. Softw. Pract. Exp. 30(13), 1465–1483 (2000)
Abel, J.: Improvements to the Burrows–Wheeler compression algorithm: After BWT stages. ACM Trans. Comput. Syst. (2003). http://www.juergen-abel.info/files/preprints/preprint_after_bwt_stages.pdf
Manzini, G.: An analysis of the Burrows–Wheeler transform. J. Acm 48(3), 407–430 (2001)
Asif Ali, M., et al.: Lossless image compression using kernel based global structure transform (GST). In: 6th international conference on emerging technologies (ICET), pp. 170–174 (2010)
Khan, A., et al.: Lossless image compression: improvement to kernel global structure transform (KGST) based Burrows–Wheeler compression algorithm (BWCA). In: 2nd international conference on machine vision (ICMV) (2010)
Balkenhol, B., Kurtz, S.: Universal data compression based on the Burrows–Wheeler transformation: theory and practice. IEEE Trans. Comput. 49(10), 1043–1053 (2000)
Schindler, M.: A fast block-sorting algorithm for lossless data compression. In: Proceedings of the IEEE data compression conference (1997)
Arnavut, Z., Magliveras, A.S.: Lexical permutation sorting algorithm. Comput. J. 40(5), 292–295 (1997)
Deorowicz, S.: Second step algorithms in the Burrows–Wheeler compression algorithm. Softw. Pract. Exp. 32(2), 99–111 (2002)
Balkenhol, B., Shtarkov, Y.M.: One attempt of a compression algorithm using the BWT. (1999)
Fenwick, P.: Block sorting text compression-final report. Technical Reports 130. University of Auckland, New Zealand, Department of Computer Science (1996)
Squeeze Chart, Lossless Data Compression Benchmark. http://www.squeezechart.com/bitmap.html
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Khan, A., Khan, A. Lossless colour image compression using RCT for bi-level BWCA. SIViP 10, 601–607 (2016). https://doi.org/10.1007/s11760-015-0783-3
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DOI: https://doi.org/10.1007/s11760-015-0783-3