Name
Abstract | ||
|---|---|---|
The adaptive image restoration is discussed based on the Genetic algorithm (GA) and Kalman filtering. We firstly use the GA to estimate the parameters of the image model according to the observed image for the Kalman filtering. The GA as an optimization strategy can adjust the model parameters adaptively and provide an appropriate model for the restoration. Furthermore, in order to get a better restored image quality, the wavelet thresholding is employed for image smoothing based on the GA results. The experimental results demonstrate that the GA and wavelet with Kalman filtering greatly improve the quality of the restored image. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74282-1_83 | ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES |
Keywords | Field | DocType |
image restoration,genetic algorithm,parameter estimation,Kalman filtering,wavelet transform | Fast Kalman filter,Pattern recognition,Computer science,Image quality,Kalman filter,Smoothing,Artificial intelligence,Image restoration,Genetic algorithm,Wavelet,Wavelet transform | Conference |
Volume | ISSN | Citations |
2 | 1865-0929 | 1 |
PageRank | References | Authors |
0.35 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fengyun Qiu | 1 | 1 | 0.35 |
| Yong Wang | 2 | 596 | 25.79 |
| Mingyan Jiang | 3 | 67 | 11.96 |
| Dongfeng Yuan | 4 | 77 | 6.83 |