Name
Abstract | ||
|---|---|---|
A powerful iterative algorithm has been developed which produces a maximum entropy solution to the image restoration problem. It has been applied to images containing up to 1024 × 1024 pixels and has been implemented on both mini and mainframe computers. Unlike some methods, the algorithm does not require the point-spread function to have any special symmetry properties. Examples are given of the application of this method both to artificially and to experimentally blurred photographs, and also to an X-ray radiograph, blurred by the size of the radiation source. For comparison, restorations of some of these images by the linear method of constrained least squares are also shown. The maximum entropy algorithm revealed detail on the images not seen in the linear restorations, but which are known to exist. Maximum entropy is also applied to the reconstruction of images from sparse data, which no comparable linear algorithm can handle. |
Year | DOI | Venue |
|---|---|---|
1983 | 10.1016/0734-189X(83)90108-1 | Computer Vision, Graphics, and Image Processing |
Keywords | DocType | Volume |
numerical method,maximum entropy,image processing,image restoration | Journal | 23 |
Issue | ISSN | Citations |
2 | 0734-189X | 27 |
PageRank | References | Authors |
32.07 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. F. Burch | 1 | 27 | 32.07 |
| S. F. Gull | 2 | 27 | 32.07 |
| John Skilling | 3 | 27 | 32.07 |