I Bandwidth Compression of Optical Images

Publisher Summary This chapter describes the concept of bandwidth compression of optical images. Because images generally contain a large amount of information, a common problem encountered in the digital transmission and storage of images is that the required channel or storage capacity is often excessive. It is desirable and sometimes mandatory to find ways to reduce this capacity requirement. The reason that this capacity reduction is possible is twofold. First, there is statistical redundancy in images; secondly, there is psycho-visual redundancy in images. Many schemes have been devised in which some of the statistical and psychovisual redundancies of images are removed to reduce the channel (storage) capacity requirement. Some of these schemes are addressed in the chapter, along with exploring that experimental studies in frameto-frame and color coding plays a growing role. On the theoretical side, it is pessimistic about seeing any significant breakthrough, although some progress may be expected through the development of refined psychovisual models and in adaptive coding systems.

[1]  D. N. Graham Image transmission by two-dimensional contour coding , 1967 .

[2]  L. C. Wilkins,et al.  Bibliography on data compression, picture properties, and picture coding , 1971, IEEE Trans. Inf. Theory.

[3]  O. J. Tretiak,et al.  Design considerations in PCM transmission of low-resolution monochrome still pictures , 1967 .

[4]  Lawrence G. Roberts,et al.  Picture coding using pseudo-random noise , 1962, IRE Trans. Inf. Theory.

[5]  P. Schultheiss,et al.  Block Quantization of Correlated Gaussian Random Variables , 1963 .

[6]  Michael P. Beddoes,et al.  Flicker effect and television compression , 1970, IEEE Trans. Inf. Theory.

[7]  G. P. Richards,et al.  The improved gray scale and the coarse-fine PCM systems, two new digital TV bandwidth reduction techniques , 1966 .

[8]  David Middleton,et al.  Sampling and Reconstruction of Wave-Number-Limited Functions in N-Dimensional Euclidean Spaces , 1962, Inf. Control..

[9]  C. M. Rader,et al.  A new vocoder conferencing scheme , 1966 .

[10]  C. Cherry,et al.  An experimental study of the possible bandwidth compression of visual image signals , 1963 .

[11]  A. J. Seyler Statistics of television frame differences , 1965 .

[12]  W. F. Schreiber,et al.  Synthetic Highs — An Experimental TV Bandwidth Reduction System , 1959 .

[13]  T. S. Huang,et al.  Research in picture processing. , 1965 .

[14]  G. P. Richards,et al.  Redundancy reduction applied to coarse-fine encoded video , 1967 .

[15]  日比,et al.  69-83画像の輪郭符号化W.F.Schreiber, T.S.Huang, O.J.Tretiak : Contour Coding of Images, WESCON'68 Technical Papers, Pt.III , 1969 .

[16]  D. Gabor,et al.  Television band compression by contour interpolation , 1961 .

[17]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[18]  Max V. Mathews,et al.  A linear coding for transmitting a set of correlated signals , 1956, IRE Trans. Inf. Theory.

[19]  William K. Pratt A bibliography on television bandwidth reduction studies , 1967, IEEE Trans. Inf. Theory.

[20]  J. O. Limb,et al.  Digital differential quantizer for television , 1969 .

[21]  J. Limb Design of dither waveforms for quantized visual signals , 1969 .

[22]  B.M. Oliver,et al.  The Philosophy of PCM , 1948, Proceedings of the IRE.

[23]  D. Huffman A Method for the Construction of Minimum-Redundancy Codes , 1952 .

[24]  Zigmantas L. Budrikis,et al.  Detail perception after scene changes in television image presentations , 1965, IEEE Trans. Inf. Theory.