| Files | Size | Format | View |
|---|---|---|---|
| Nee2002Sep1WInHDWavel.PDF | 700.0Kb | application/pdf |
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| dc.contributor.author | Neelamani, Ramesh Nowak, Robert David Baraniuk, Richard G. |
|---|---|
| dc.creator | Neelamani, Ramesh Nowak, Robert David Baraniuk, Richard G. |
| dc.date.accessioned | 2007-10-31T00:55:40Z |
| dc.date.available | 2007-10-31T00:55:40Z |
| dc.date.issued | 2002-10-20 |
| dc.date.submitted | 2002-10-02 |
| dc.identifier.uri | http://hdl.handle.net/1911/20144 |
| dc.description | Journal Paper |
| dc.description.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. |
| dc.description.sponsorship | National Science Foundation |
| dc.description.sponsorship | National Science Foundation |
| dc.description.sponsorship | Air Force Office of Scientific Research | dc.subject | inverse halftoning error diffusion deconvolution wavelets wavelet-vaguelette |
| dc.subject.other | Image Processing and Pattern analysis Wavelet based Signal/Image Processing |
| dc.title | WInHD: Wavelet-based Inverse Halftoning via Deconvolution |
| dc.type | Journal Paper |
| dc.citation.bibtexName | article |
| dc.citation.journalTitle | IEEE Transactions on Image Processing |
| dc.date.modified | 2002-10-16 |
| dc.contributor.center | Digital Signal Processing (http://dsp.rice.edu/) |
| dc.subject.keyword | inverse halftoning error diffusion deconvolution wavelets wavelet-vaguelette |
| dc.relation.project | http://www.dsp.rice.edu/software/winhd.shtml |
| dc.relation.software | http://www.dsp.rice.edu/software/winhd.shtml |
| dc.identifier.citation | R. Neelamani, R. D. Nowak and R. G. Baraniuk, "WInHD: Wavelet-based Inverse Halftoning via Deconvolution," IEEE Transactions on Image Processing, 2002. |