(14-15(02)) * << * >> * Russian * English * Content * All Issues

Variable quantization with minimal distortion
V.B. Tkhor

 PDF, 4944 kB

Pages: 143-156.

Full text of article: Russian language.

Abstract:
When dealing with various scientific and engineering issues one has to transmit, store or process a huge amount of visual information, which is apparently the most conventional for a human from the psychological point of view. As soon as the volumes of visual information begin to exceed the capabilities of technical systems of information transmission, storage or processing, a need for the compression arises. The major operation responsible for the quality of the decoded image is quantization that divides the space of signals into cells.

Citation:
Tkhor VB. Variable quantization with minimal distortion. Computer Optics 1995; 14-15(2): 143-156.

References:
  1. Shannon K. A mathematical theory of communication. Works on information science and cybernetics. Moscow: IL; 1963; 243 - 332.
  2. Berger Т. Rate-Distortion Theory. Englewood Clifs. N.J.: Prentice-Hall; 1971.
  3. Kolmogorov AN, Tikhomirov VN. Epsilon-entropy and epsilon-capacity of sets in function spaces. Uspekhi Matematicheskikh Nauk. 1959; 14; 3.
  4. Kieffer JC. A Survey of the Theory of Source Coding with a Fidelity Criterion; IEEE Transactions on Inform. Theory; 1993: 39(5).
  5. Tasto M, Wintz P. A bound on the rate-distortion function and application to images; IEEE Trans. on Inf. Theory; 1972; IT-18: 150-159.
  6. Anastassiou D, Sakrison D. New Bounds to R(D) for Additive Sources and Applications to Images Encoding, IEEE Trans. on Inf. Theory; 1979; IT-25(2): 145-154.
  7. Sakrison DJ. On the role of the observer and a distortion measure in image transmission, IEEE Trans. Comm.; 1977; COM-25: 1251-1267.
  8. Granrath DJ. The role of human visual models in image processing; Proceedings of the IEEE; 1981; 69(5): 552-561.
  9. Hall CF, Hall EL. A nonlinear model for spacial characteristics of the human visual system, IEEE Trans. Syst. Man Cybern.; 1977; SMC-7: 161-170.
  10. Mannos JL, Sakrison DJ. Effects of a Visual Fidelity Criterion on the Encoding of Images, IEEE Trans, on Inform. Theory; 1974; IT-20(4): 525-535.
  11. Kronander T. Perception based image coding. Proceedings of SSAB; Gothenburg, Sweden: 1989.
  12. Jain AK. Compression of video information. A review; TIIER; 1981; 69(3): 71-117.
  13. Netravali A, Limb J. Image coding. A review; TIIER; 1980; 68(3): 76-121.
  14. Pratt W. Digital image processing; Moscow: Mir Publisher; 1982; 1: 312; 2: 480.
  15. Jayant N. Signal Compression: Technology Targets and Research Directions; IEEE Journal on Selected Areas in Communications; 1992; 10(5).
  16. Goodall WM. Television by pulse code modulation; Bell Syst. Techn. J.; 1951; 30: 33-49.
  17. Inventor's Certificate 120534. The method of analysis and synthesis of television images. Braude-Zolotarev YM. Application 22.11.1957; Publ. 1959; Bull. 12.
  18. Cutler CC. Differential quantization on communication signals; U.S. Patent 2605361; 1952.
  19. Kretzmer ER. Reduced alphabet representation of television signals, Conv. Rec. IRE; 1958; 6: 58.
  20. Schreiber WF, Knapp CF. Bandwidth reduction by digital coding, Conv. Rec. IRE; 1958; 6: 58.
  21. Kishimoto Т, Mitsua E, Hoshida КA. Method of still picture coding by using statistics properties; National Conference of the Inst. of Electronics and Communications of Japan; 1974; 974.
  22. Delp EJ, Mitchel OR. Image compression using block truncation coding; IEEE Trans. Communs; 1979; COM-27: 1335-1342.
  23. Sardyko SV, Zuckerman II. Run-length encoding of images. Technique of film and television; 1977; 9: 52-54.
  24. Tkhor VB. Adaptive image quantization, data processing in information systems; Moscow: 1986; 1: 40-43.
  25. Tkhor VB. Comparison of methods of three-level block quantization of images. Redundancy reduction in digital TV system. Abstracts of reports of All-union symposium; Tbilisi: 1983; 86-87.
  26. Tkhor VB, Gogoberidze LI. Three-level group image encoding, Digital image encoding and image switching, Proceedings of the State Pedagogical Institute named after V.I. Lenin; 1985; 10(292): 55-58
  27. Tkhor VB. Coding of Gauss-Markov fields by the method of block pulse code modulation. Data processing in information systems; Moscow:1986; 11: 28-31.
  28. Tkhor VB, Gogoberidze LI. Block pulse code modulation and source properties, Digital coding and switching of image signals, Proceedings of the State Pedagogical Institute named after V.I. Lenin; 1987; 613(8): 75-78.
  29. Lebedev DS, Tkhor VB. Interpolation approach to image coding by block PCM method. Abstracts of papers of the Eleventh All- Union Conference Automated image processing systems - 86; 1986; 91-93.
  30. Lebedev DS, Tkhor VB. Interpolation approach to block pulse code modulation, Iconics. Coding and image processing; Moscow: Nauka Publisher; 1988; 5-21.
  31. Tkhor VB. Coding of images with variable quantization parameters in video processing systems. Dissertation for the degree of candidate of technical sciences; Moscow: 1988.
  32. inventor's certificate 1359914. A method of encoding and decoding a television signal / Tkhor VB. Application 08.07.1985 Publ. 1987. Bull. 46.
  33. Tkhor VB. Approximation approach to adaptive image quantization. Information transfer and processing systems. Part 1; Moscow: 1988.
  34. Digital coding of images. Ed. Zuckerman II; Moscow: Radio i svyaz; 1981; 239.
  35. Pilipchuk NI, Yakovlev VP. Adaptive pulse code modulation, Moscow: Radio i svyaz; 1986; 296.
  36. Yiyan W, Coll D. Single bit-map block truncation coding of color images; IEEE Journal on Selected Areas in Communications; 1992; 10(5).
  37. Monet P, Dubois E, Block adaptive quantization of images; IEEE Transactions on Communications; 1993; 41(2).
  38. Lebedev DS, Bezruk AA, Novikov VM. Markov model of image and drawing; Preprint The institute for information transmission problems of the USSR Academy of sciences; Moscow: 1983; 40.
  39. Lebedev DS. A statistical model of an image. Iconics. Spatial Filtering of Images. Photographic Systems; Moscow: Nauka Publisher; 1970: 53-65.
  40. Lebedev DS. Statistical theory of video processing. Handbook. Moscow Institute of Physics and Technology; Moscow: 1988.
  41. De Boor C. A practical guide to splines; Moscow: Radio i svyaz; 1985; 303.
  42. Max J. Quantizing for minimum distortion, IRE Trans. on Information Theory; 1960; IT-6: 7-12 .

© 2009, IPSI RAS
151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: journal@computeroptics.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20