VESTNIK of Samara University. Aerospace and Mechanical EngineeringVESTNIK of Samara University. Aerospace and Mechanical Engineering2542-04532541-7533Samara National Research University208410.18287/1998-6629-2014-0-3(45)-159-167UnknownMethod of compression of digital halftone images on the basis of markov chains with several statesPetrovE. P.<p>Doctor of Science (Engineering), Professor</p>
<p>Head of the Department of Radio Electronic Means</p>EPetrov@mail.ruHarinaN. L.<p>Candidate of Science (Engineering)</p>
<p>Associate Professor, Department of Radio Electronic Means</p>Natal_res@mail.ruRzhanikovaE. D.<p>Postgraduate student</p>lavrova_elena@bk.ruVyatka State University160920151431591672201201522012015Copyright © 2015, VESTNIK of the Samara State Aerospace University2015<p>The paper presents a mathematical model (MM) of a digital halftone image (DHI) on the basis of a two-dimensional Markov chain with several states; its adequacy to real images is analyzed. On the basis of MM a method of DHI compression is developed. The method provides separation of DHI into binary images with subsequent combining of two digits in a plane. Each plane is considered as a two-dimensional random Markov process with several (N=4) states. On the basis of the theory of random Markov processes prediction of the plane elements is carried out. All incorrectly predicted elements are located in a bit stream and serve as a reference for the recovery of the image. Separation of areas containing background noise with a structure similar to the white gaussian noise (WGN) is carried out beforehand for the planes containing low- order bits, these areas are not stored, they are filled with WGN samples in case of restoration. The efficiencyof the method is no inferior to that of known methods of compression based on DCT or DWT, it does not involve computing operations and makes it possible to work with multidigital images (8 and more digits) without increase in the time of compression due to parallel processing of the planes.</p>Mathematical modelMarkov chaindigital halftone imagematrix of transition probabilitiesimage compressionМатематическая модельцепь Марковацифровое полутоновое изображениематрица вероятностей переходасжатие изображений[1. Shvedov A.S. On Markov Chain Monte Carlo Methods // Higher School of Economics Economic Journal. 2010. V. 14, no. 2. P. 227-243. (In Russ.)][2. Kemeny J.G., Snell J.L., Knapp A.W. Denumerable Markov Chains: Trans. from Engl. Moscow: Nauka Publ., 1987. 416 p.][3. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E. Equation of State Calculations by Fast Computing Machines // Journal of Chemical Physics. 1953. No. 21. P.1087-1092. DOI: <a href='http://doi.org/10.2172/4390578'>10.2172/4390578</a>][4. Gelfand A.E., Smith A.F.M. Sampling-based Approaches to Calculating Marginal Densities // Journal of the American Statistical Association. 1990. No. 85. P. 398-409. DOI: <a href='http://doi.org/10.2307/2289776'>10.2307/2289776</a>][5. Tichonov V.I., Mironov M.A. Markovskie protsessy [Markov processes]. Moscow: Sov. radio Publ., 1977. 488 p.][6. Petrov Е.P., Harina N.L., Rzanikova Е.D. Model of Markov chain with several states // Proc. 10th Int. Conf. «Physics and radioelectronics in medicine and ecology», Book 1. Vladimir. 2012. P. 211-215. (In Russ.)][7. Petrov Е.P., Harina N.L., Rzanikova Е.D. Method of compression of digital grayscale images on the basis of Markov's chains with several states // Proc. 10th Int. Conf. «Digital processing of signals and its application – DSPA-2013», Moscow: RNTORES imeni A.S. Popova Publ., 2013. P. 132-135. (In Russ.)]