Abstract
Deconvolution results may deviate true answers because of noise and low pass filtering. The effects of noise and blurred function to image data are compared and studied for several common deconvolution algorithms, and the maximum likelihood algorithm based on the Poisson-Markov model of super-resolution image restoration algorithms is proposed. Experiments showed that, based on the MPML algorithm proposed, it has the advantages of diminishing losses of original data in contrast to other algorithms, especially in cases involving lower noise. The recovery images display very small concussive lines and have better super-resolution recovery ability for deconvolution applications.
Original language | English |
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Pages (from-to) | 905-909 |
Number of pages | 5 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 24 |
Issue number | 10 |
Publication status | Published - Oct 2004 |
Keywords
- Deconvolution
- Image reconstruction
- MPML algorithm