Devolopment of lossless image compression algorithms based on the analysis of brightness differences

1Rusyn, BP, 2Mosorov, VYa.
1Karpenko Physico-Mechanical Institute of the National Academy of Science of Ukraine, Lviv, Ukraine
2National University «Lviv Polytechnic», Lviv, Ukraine
Kosm. nauka tehnol. 1999, 5 ;(5):16–20
https://doi.org/10.15407/knit1999.05.016
Section: Study of the Earth from Space
Publication Language: Ukrainian
Abstract: 
We discuss the lossless image compression algorithms which are used in the modern data base communication systems for upgrading the efficiency of the channels with insufficient transmitting capacity. A new approach is proposed for lossless compression in which the image decorrelation is based on the analysis of brightness differences, coding of most significant digits in neighboring pixels, and interpolation, without recourse to the hierarchical image decomposition. These algorithms were compared with well-known hierarchical algorithms for lossless compression.
Keywords: data base communication systems, image decorrelation, lossless image compression
References: 
1. Mosorov V. Ya. Hierarchic algorithm for compression of graphic information. In: Proc. 2nd Int. Conference Computer Technologies in Printing, Oct. 1998, Lviv, Ukraine, 47—48 (Lviv, 1998) [In Ukrainian].
2. Rusyn B. P. Systems synthesis, processing and recognition of complex structured image, 264 p. (Vertical, Lviv, 1997) [In Ukrainian].
3. Rusyn B. P., Mosorov V. Ya. The development of lossless image data compression algorithms for modern telecommunication systems. In: Proc. IV Int.Conference NTK-Telecom-99, Odessa, Sept. 1999, 607— 610 (1999) [In Ukrainian].
4. Howard P., Vitter J. New methods for lossless image compression using arithmetic coding. J. Info. Proc@Manag., 28 (5), 765—779 (1992).
5. Huffman D. A. A method for the construction of minimum-redundansy codes. Proc. IRE, 40, 1098— 1101 (1952).
6. Jain A. K. Image data compression: A review. Proc IEEE, 69, 349—389 (1981).
7. Lee H. S., Kim Y., Oh S. Lossless compresion of medical images by predication and classification. Opt. Eng., 33, 160—166 (1994).