Adaptive Threshold Modulation for Error Diffusion Halftoning

Grayscale digital image halftoning quantizes each pixel to one bit. In error diffusion halftoning, the quantization error at each pixel is filtered and fed back to the input in order to diffuse the quantization error among the neighboring grayscale pixels. Error diffusion introduces nonlinear distortion (directional artifacts), linear distortion (sharpening), and additive noise. Threshold modulation, which alters the quantizer input, has been previously used to reduce either directional artifacts or linear distortion. This paper presents an adaptive threshold modulation framework to improve halftone quality by optimizing error diffusion parameters in the least squares sense. The framework models the quantizer implicitly, so a wide variety of quantizers may be used. Based on the framework, we derive adaptive algorithms to optimize 1) edge enhancement halftoning and 2) green noise halftoning. In edge enhancement halftoning, we minimize linear distortion by controlling the sharpening control parameter. We may also break up directional artifacts by replacing the thresholding quantizer with a deterministic bit flipping (DBF) quantizer. For green noise halftoning, we optimize the hysteresis coefficients.

[1]  Ping Wah Wong,et al.  Adaptive error diffusion and its application in multiresolution rendering , 1996, IEEE Trans. Image Process..

[2]  J. Jarvis,et al.  A New Technique for Displaying Continuous Tone Images on a Bilevel Display , 1976, IEEE Trans. Commun..

[3]  Keith T. Knox.  Threshold modulation in error diffusion on nonstandard rasters , 1994, Electronic Imaging.

[4]  Gonzalo R. Arce,et al.  Green noise digital halftoning , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[5]  Reiner Eschbach,et al.  Threshold modulation in error diffusion , 1993, J. Electronic Imaging.

[6]  John J. Paulos,et al.  An analysis of nonlinear behavior in delta-sigma modulators , 1987 .

[7]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[8]  Robert Ulichney,et al.  Digital Halftoning , 1987 .

[9]  Alan C. Bovik,et al.  Design and quality assessment of forward and inverse error diffusion halftoning algorithms , 1998 .

[10]  Robert Ulichney,et al.  Dithering with blue noise , 1988, Proc. IEEE.

[11]  John F. Jarvis,et al.  A survey of techniques for the display of continuous tone pictures on bilevel displays , 1976 .

[12]  Reiner Eschbach,et al.  Limit cycle behavior of error diffusion , 1994, Proceedings of 1st International Conference on Image Processing.

[13]  Alan C. Bovik,et al.  Modeling and quality assessment of halftoning by error diffusion , 2000, IEEE Trans. Image Process..

[14]  Alan C. Bovik,et al.  Digital halftoning as 2-D delta-sigma modulation , 1997, Proceedings of International Conference on Image Processing.

[15]  Patrick L. Combettes,et al.  Adaptive linear filtering with convex constraints , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[16]  R. Schreier,et al.  Delta-sigma data converters : theory, design, and simulation , 1997 .

[17]  Reiner Eschbach,et al.  Error-diffusion algorithm with edge enhancement , 1991 .

[18]  Mark Sandler,et al.  A sigma-delta modulator topology with high linearity , 1997, Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS '97.

[19]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[20]  Neal,et al.  Using Peano Curves for Bilevel Display of Continuous-Tone Images , 1982, IEEE Computer Graphics and Applications.

[21]  Keith T. Knox.  Error image in error diffusion , 1992, Electronic Imaging.

[22]  Niranjan Damera-Venkata,et al.  Design and analysis of vector color error diffusion halftoning systems , 2001, IEEE Trans. Image Process..

[23]  G. Temes.  Delta-sigma data converters , 1994 .