A perceptually motivated three-component image model-part II: applications to image compression

For past I see ibid., vol.4, no.4, p.405 (1995). The use of the image model of Part I is investigated in the context of image compression. The model decomposes the image into a primary component that contains the strong edge information, a smooth component that represents the background slow-intensity variations, and a texture component that contains the textures. The primary component, which is known to be perceptually important, is encoded separately by encoding the intensity and geometric information of the strong edge brim contours. Two alternatives for coding the smooth and texture components are studied: entropy-coded adaptive DCT and entropy-coded subband coding. It is shown via simulations that the proposed schemes, which can be thought of as a hybrid of waveform coding and feature-based coding techniques, result in both subjective and objective performance improvements over several other image coding schemes and, in particular, over the JPEG continuous-tone image compression standard. These improvements are especially noticeable at low bit rates. Furthermore, it is shown that a perceptual tuning based on the contrast-sensitivity of the human visual system can be used in the DCT-based scheme, which in conjunction with the three-component model, leads to additional subjective performance improvements.

[1]  William K. Pratt,et al.  Scene Adaptive Coder , 1984, IEEE Trans. Commun..

[2]  Murat Kunt,et al.  Recent results in high-compression image coding (Invited Papaer) , 1987 .

[3]  M. Kunt,et al.  Second-generation image-coding techniques , 1985, Proceedings of the IEEE.

[4]  Jerry D. Gibson,et al.  Distributions of the Two-Dimensional DCT Coefficients for Images , 1983, IEEE Trans. Commun..

[5]  Li-Sheng Wang,et al.  CONSOLE User's Manual. , 1987 .

[6]  Gregory K. Wallace,et al.  The JPEG still picture compression standard , 1991, CACM.

[7]  Herbert Gish,et al.  Asymptotically efficient quantizing , 1968, IEEE Trans. Inf. Theory.

[8]  Xiaonong Ran,et al.  A Three-Component Image Model Based on Human Visual Perception and Its Applications in Image Coding and Processing , 1992 .

[9]  Thomas S. Huang.  Coding of Two-Tone Images , 1977, IEEE Trans. Commun..

[10]  J. M. Shapiro.  An embedded wavelet hierarchical image coder , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  R. J. Safranek,et al.  A perceptually tuned sub-band image coder with image dependent quantization and post-quantization data compression , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[12]  James W. Modestino,et al.  Adaptive entropy coded subband coding of images , 1992, IEEE Trans. Image Process..

[13]  Nariman Farvardin,et al.  A Perceptually Motivated Three-Component Image Model , 1996 .

[14]  C. Smith,et al.  Adaptive Coding of Monochrome and Color Images , 1977, IEEE Trans. Commun..

[15]  Herbert Freeman,et al.  On the Encoding of Arbitrary Geometric Configurations , 1961, IRE Trans. Electron. Comput..

[16]  A. Habibi,et al.  Image Coding by Linear Transformation and Block Quantization , 1971 .

[17]  Michel Barlaud,et al.  Image coding using wavelet transform , 1992, IEEE Trans. Image Process..

[18]  Nariman Farvardin,et al.  Trellis-based scalar-vector quantizer for memoryless sources , 1994, IEEE Trans. Inf. Theory.

[19]  Nariman Farvardin,et al.  Combined VQ-DCT coding of images using interblock noiseless coding , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[20]  Mark J. T. Smith,et al.  A three-source multirate model for image compression , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[21]  Min Wang,et al.  Entropy-constrained trellis-coded quantization , 1992, IEEE Trans. Inf. Theory.

[22]  Nariman Farvardin,et al.  Subband Image Coding Using Entropy-Coded Quantization over Noisy Channels , 1992, IEEE J. Sel. Areas Commun..

[23]  Nasser M. Nasrabadi,et al.  Image coding using vector quantization: a review , 1988, IEEE Trans. Commun..

[24]  Stefan Carlsson,et al.  Sketch based coding of grey level images , 1988 .

[25]  Michael W. Marcellin,et al.  Wavelet coding of images using trellis-coded quantization , 1992, Defense, Security, and Sensing.

[26]  J. Yan,et al.  Encoding of Images Based on a Two-Component Source Model , 1977, IEEE Trans. Commun..

[27]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[28]  C. Rubinstein,et al.  On the Design of Quantizers for DPCM Coders: A Functional Relationship Between Visibility, Probability and Masking , 1978, IEEE Trans. Commun..

[29]  Alan C. Bovik,et al.  Visual pattern image coding , 1990, IEEE Trans. Commun..

[30]  Nariman Farvardin,et al.  A perceptually motivated three-component image model-Part I: description of the model , 1995, IEEE Trans. Image Process..

[31]  Nariman Farvardin,et al.  Adaptive DCT image coding based on a three-component image model , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[32]  David J. Sakrison,et al.  The effects of a visual fidelity criterion of the encoding of images , 1974, IEEE Trans. Inf. Theory.

[33]  David L. Neuhoff,et al.  A rate and distortion analysis of chain codes for line drawings , 1985, IEEE Trans. Inf. Theory.

[34]  B. Prasada,et al.  Adaptive quantization of picture signals using spatial masking , 1977, Proceedings of the IEEE.

[35]  William A. Pearlman.  Adaptive cosine transform image coding with constant block distortion , 1990, IEEE Trans. Commun..

[36]  M. G. Perkins,et al.  A psychophysically justified bit allocation algorithm for subband image coding systems , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[37]  David G. Luenberger,et al.  Linear and nonlinear programming , 1984 .

[38]  Ian H. Witten,et al.  Arithmetic coding for data compression , 1987, CACM.

[39]  H. Gharavi,et al.  Sub-band coding of monochrome and color images , 1988 .

[40]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[41]  Christopher F. Barnes,et al.  Image coding with variable rate RVQ , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[42]  N. Jayant,et al.  Digital Coding of Waveforms: Principles and Applications to Speech and Video , 1990 .

[43]  John W. Woods,et al.  Subband coding of images , 1986, IEEE Trans. Acoust. Speech Signal Process..

[44]  Nariman Farvardin,et al.  A Three-component Image Model For Coding With A Subjective Criterion , 1991, Proceedings of the Seventh Workshop on Multidimensional Signal Processing.

[45]  Jorma Rissanen,et al.  Generalized Kraft Inequality and Arithmetic Coding , 1976, IBM J. Res. Dev..

[46]  J. Robson,et al.  Application of fourier analysis to the visibility of gratings , 1968, The Journal of physiology.

[47]  A.N. Netravali,et al.  Picture coding: A review , 1980, Proceedings of the IEEE.

[48]  Peter H. Westerink,et al.  Subband coding of images using vector quantization , 1988, IEEE Trans. Commun..

[49]  Bhaskar Ramamurthi,et al.  Classified Vector Quantization of Images , 1986, IEEE Trans. Commun..

[50]  Nariman Farvardin,et al.  Optimum quantizer performance for a class of non-Gaussian memoryless sources , 1984, IEEE Trans. Inf. Theory.

[51]  Jan Biemond,et al.  Subband Coding of Color Images , 1991 .