- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
WAVELET-BASED FILLING-IN IN A DECOMPOSITION SPACE OF REGULARLY OR IRREGULARLY SAMPLED IMAGE | ||
| AL-TAQANI | ||
| Article 1, Volume 19, Issue 2, 2006, Pages 72-84 | ||
| Author | ||
| Abstract | ||
| Wavelet-Network (W N) model has been very recently proposed and applied to image processing. In this paper a general model is proposed for the reconstruction of the lost blocks of the irregularly sampled image.The proposed model is fast and it uses the correlation between the lost block and its neighbors. An algorithm is introduced which uses first thresholding to determine the presence or absence of edges in the lost block. The interpolation scheme minimizes the square of the error between the border coefficients of the lost block and those of its neighbors. The proposed method is able to improve image quality in terms of both visual perception and image fidelity The architecture of the proposed neural network is fast forward multilayer perceptron and in it’s learning it uses the resilient back-propagation training. The reconstruction error is expressed in terms of (PSNR) When it is viewed on a monitor, there is virtually no difference between the original and the image reconstructed using the proposed method. | ||
|
Statistics Article View: 121 PDF Download: 63 |
||