Name
Abstract | ||
|---|---|---|
High precision MTF measurement is the basis of high quality image restoration. Since the presence of noise in images, traditional MTF measurement based on Target image will produce biased result, and the biased result will introduce new noise after image restoration. In this paper, based on analysis of characteristics and limitation of traditional image restoration methods, we propose an image restoration approach based on Kalman filter, this approach firstly uses Gaussian fitting to obtain theoretical value of line spread function, then it uses KALMAN filter to obtain the true value of line spread function from theoretical value and measured value. Experiments on TDI-CCD images show that the approach proposed in this paper make better performance. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IGARSS.2013.6721201 | IGARSS |
Keywords | Field | DocType |
kalman filter,kalman filters,optical variables measurement,line spread function,modulation transformation function,optical images,image restoration,gaussian fitting,mtf,noise component,optical transfer function,optical information processing,mtf measurement,tdi-ccd images,fitting,remote sensing,satellites | Computer vision,Optical transfer function,Fast Kalman filter,Computer science,Remote sensing,Kalman filter,Gaussian,Artificial intelligence,Image restoration,Line Spread Function | Conference |
Volume | Issue | ISSN |
null | null | 2153-6996 |
ISBN | Citations | PageRank |
978-1-4799-1114-1 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bingxian Zhang | 1 | 0 | 0.34 |
| mi | 2 | 88 | 30.02 |
| Jun Pan | 3 | 28 | 6.90 |