ANALYSIS OF THE EFFICIENCY OF DATA COMPRESSION IN A THREE-DIMENSIONAL SCANNING SYSTEM USING THE RLE ALGORITHM
Abstract
Summary – the techniques used to compress data allow a bigger transfer of information due to the processing that is performed, by means of numerical and statistical transformations, it is possible to represent the same information in a smaller space. One of the main problems that exist in communications systems lies in the use of the channel. The current studies focus on the study of the characteristics and effects of the noise present in the channel and the disturbances generated in the transmitted information. This paper studies the efficiency of the Run Length Encoding (RLE) compression algorithm in a wired communication channel, by measuring some parameters it is possible to determine the efficiency of the use of the channel, using the RLE algorithm, a methodology is used for the study, which allows determining the efficiency of the use of the channel, prior to the use of the compression algorithm and afterwards, in this way it is possible to determine the efficiency of the use of the channel, in this work, there is an increase in the use of the channel due to the RLE compression algorithm.
References
D. A Gudeto Salomon, Data Compression Methods, New York: Springer Verlag, 2002.
S. HAYKIN, Digital Communication, John Wiley Sons, 1988.
S. Haykin, Communication Systems, McMaster University: John Wiley Sons, 2001.
B. Sklar, Digital Communications, Fundamentals and Communications, Prentice Hall, 2001.
J. Proakis and M. Salehir, Communication Systems Engineering, Upper Saddle River, New Jersey 07458: Prentice Hall, 2002.
A. S. William and . A. Pearlman, Digital Signal Compression, Cambridge University Press, 2011.
D. Salomon, A guide to Data Compression Methods, Springer, 2002.
B. M. a. J. Abrahams, "On the redundancy of optimal binary prefix-condition codes for finite and infinite sources," IEEE Transactions on Information Theory, vol. 33, no. 1, pp. 156-160, Jan. 1987.
B. M. J. E., Transmisión de Datos, ULA: Taller de Publicaciones de la Facultad de Ingeniería, 2005.
J. Fowler and . R. Yagel, Lossless Compression of Volume Data, Symposium on Volume Visualization, 2007.
K. S. N. M. J. D. a. P. J. M. T. Asif, "Near-Lossless Compression for Large Traffic Networks," IEEE Transactions on Intelligent Transportation Systems, vol. vol. 16, no. no. 4, pp. pp. 1817-1826, Aug. 2015.
P. D. Symes, Video Compression, McGraw-Hill, 1998.
S. B., C. A. Bibyk Kenneth and M. J. Shalkhausert, Digital Compression Algorithmsf For Hdtv Transmission, The Ohio State University Columbus: Dept. of Electrical Engineering.
Y. W. W. X. a. Q. D. J. Yang, "Image Coding Using Dual-Tree Discrete Wavelet Transform," IEEE Transactions on Image Processing, vol. 17, no. 9, pp. 1555-1569, Sept. 2008..
E. h. Y. a. L. Wang, "Joint Optimization of Run-Length Coding, Huffman Coding, and Quantization Table With Complete Baseline JPEG Decoder Compatibility," IEEE Transactions on Image Processing, vol. 18, no. 1, pp. 63-74, 2009.
J. M. H. Madrid, Caracterización de Algortimos de Compresión de Datos en la Comunicación de un Sistema de Detección de Defectos, Puebla, México, 2014.
B. J. a. W. P. Burleson, "Real-time VLSI compression for high-speed wireless local area networks," Data Compression Conference, pp. pp. 431-., 1995.
D. W. Jones, "Practical evaluation of a data compression algorithm," in Data Compression Conference,, Snowbird, UT, 1991.