A novel neural network based method for halftoning and inverse halftoning of digital images is presented. We first start from inverse half-toning of images produced from error diffusion methods using a RBF Network plus a MLP network. The restored contone images have had good quality already. Then, a SLP neural network is used to refine the halftoning processing and the training process of the inverse half-toning network is also involved. The combined training procedure produces half-tone images and the corresponding continuous tone images at the same time. It is found that these contone images have even better PSNR performance. Furthermore, the resulted half-tone images are visually sharper and clearer, too. The proposed inverse half-toning method is also compared to the well-known LUT method.
|Number of pages||4|
|Journal||Proceedings - International Conference on Image Processing, ICIP|
|Publication status||Published - 2004|
|Event||2004 International Conference on Image Processing, ICIP 2004 - , Singapore|
Duration: 2004 Oct 18 → 2004 Oct 21
All Science Journal Classification (ASJC) codes