Coupled nonlinear-diffusion color image sharpening based on the chromaticity-brightness model

Takahiro Saito; Reina Nosaka D.V.M.; Takashi Komatsu

doi:10.1117/12.641330

19 January 2006 Coupled nonlinear-diffusion color image sharpening based on the chromaticity-brightness model

Takahiro Saito, Reina Nosaka D.V.M., Takashi Komatsu

Proceedings Volume 6077, Visual Communications and Image Processing 2006; 60771H (2006) https://doi.org/10.1117/12.641330
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

Abstract

Previously we have presented a selective image sharpening method based on the coupled nonlinear diffusion process composed of a nonlinear diffusion term, a fidelity term and an isotropic peaking term, and it can sharpen only blurred edges without increasing the noise visibility. Our previously presented prototypal color-image sharpening methods based on the coupled nonlinear-diffusion process have been formulated on the linear color models, namely, the channel-bychannel model and the 3D vectorial model. Our prototypal methods can sharpen blurred color step edges, but they do not necessarily enhance contrasts of signal variations in complex texture image regions so well as in simple step-edge regions. To remedy the drawback, this paper extends our coupled nonlinear-diffusion color-image sharpening method to the nonlinear non-flat color model, namely, the chromaticity-brightness model, which is known to be closely relating to human color perception. We modify our time-evolution PDE's for the non-flat space of the chromaticity vector and present its digital implementations. Through experimental simulations, we compare our new color-image sharpening method based on the chromaticity-brightness model with our prototypal color-image sharpening methods based on the linear color models.

Citation Download Citation

Takahiro Saito, Reina Nosaka D.V.M., and Takashi Komatsu "Coupled nonlinear-diffusion color image sharpening based on the chromaticity-brightness model", Proc. SPIE 6077, Visual Communications and Image Processing 2006, 60771H (19 January 2006); https://doi.org/10.1117/12.641330

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KEYWORDS

3D modeling

RGB color model

Diffusion

Image processing

Bromine

Argon

Human vision and color perception

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