Adaptive methods for dithering color images

Most color image printing and display devices do not have the capability of reproducing true color images. A common remedy is the use of dithering techniques that take advantage of the lower sensitivity of the eye to spatial resolution and exchange higher color resolution with lower spatial resolution. An adaptive error diffusion method for color images is presented. The error diffusion filter coefficients are updated by a normalized least mean square-type (LMS-type) algorithm to prevent textural contours, color impulses, and color shifts, which are among the most common side effects of the standard dithering algorithms. Another novelty of the new method is its vector character: previous applications of error diffusion have treated the individual color components of an image separately. We develop a general vector approach and demonstrate through simulation studies that superior results are achieved.

[1]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

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

[3]  Michael T. Orchard,et al.  Color quantization of images , 1991, IEEE Trans. Signal Process..

[4]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

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

[6]  Jan P. Allebach,et al.  Quantization and multilevel halftoning of color images for near-original image quality , 1990 .

[7]  Avideh Zakhor,et al.  A new class of B/W and color halftoning algorithms , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[8]  David L. Neuhoff,et al.  Printer models and error diffusion , 1995, IEEE Trans. Image Process..

[9]  Paul S. Heckbert Color image quantization for frame buffer display , 1982, SIGGRAPH.

[10]  Barry L. Shoop,et al.  Optimal error diffusion for digital halftoning using an optical neural network , 1994, Proceedings of 1st International Conference on Image Processing.

[11]  Ping Wah Wong Error diffusion with dynamically adjusted kernel , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

[12]  R. K. Kunchev,et al.  Adaptive error diffusion method for image quantisation , 1993 .

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