|
Title:
|
WInHD: Wavelet-based Inverse Halftoning via Deconvolution |
|
Author:
|
Neelamani, Ramesh; Nowak, Robert David; Baraniuk, Richard G. |
|
Type:
|
Journal Paper |
|
Keywords:
|
inverse halftoning; error diffusion; deconvolution; wavelets; wavelet-vaguelette |
|
Citation:
|
R. Neelamani, R. D. Nowak and R. G. Baraniuk, "WInHD: Wavelet-based Inverse Halftoning via Deconvolution," IEEE Transactions on Image Processing, 2002. http://hdl.handle.net/1911/20144. |
|
Center:
|
Digital Signal Processing
|
|
Abstract:
|
We propose the Wavelet-based Inverse Halftoning via Deconvolution (WInHD) algorithm to perform inverse halftoning of error-diffused halftones. WInHD is motivated by our realization that inverse halftoning can be formulated as a deconvolution problem under Kite et al.'s linear approximation model for error diffusion halftoning. Under the linear model, the error-diffused halftone comprises the original gray-scale image blurred by a convolution operator and colored noise; the convolution operator and noise coloring are determined by the error diffusion technique. WInHD performs inverse halftoning by first inverting the model-specified convolution operator and then attenuating the residual noise using scalar wavelet-domain shrinkage. Since WInHD is model-based, it is easily adapted to different error diffusion halftoning techniques. Using simulations, we verify that WInHD is competitive with state-of-the-art inverse halftoning techniques in the mean-squared-error sense and that it also provides good visual performance. We also derive and analyze bounds on WInHD's mean-squared-error performance as the image resolution increases. |
|
URI:
|
http://hdl.handle.net/1911/20144
|
|
Date Published:
|
2002-10-20 |