Name
Abstract | ||
|---|---|---|
In this paper, we present a new method for texture classification which we call the regularized simultaneous autoregressive method (RSAR). The regularization technique is introduced. With the technique, the new algorithm RSAR outperforms the traditional algorithm in texture classification. Particularly, our new algorithm is useful for extracting texture from the image which is coarse or contains too much noise. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ISCAS.2003.1205784 | ISCAS (4) |
Keywords | Field | DocType |
regularized simultaneous ar method,texture classification,regularized simultaneous autoregressive model,autoregressive processes,image classification,image texture,image texture extraction,remote sensing,classification algorithms,data mining,pixel,maximum likelihood estimation,autoregressive model,integral equations,least squares approximation | Least squares,Autoregressive model,Pattern recognition,Computer science,Image texture,Image processing,Regularization (mathematics),Pixel,Artificial intelligence,Statistical classification,Contextual image classification | Conference |
Volume | ISBN | Citations |
4 | 0-7803-7761-3 | 2 |
PageRank | References | Authors |
0.40 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaowei Wang | 1 | 134 | 29.62 |
| Yanfei Wang | 2 | 89 | 17.61 |
| Wen Gao | 3 | 11374 | 741.77 |
| Yong Xue | 4 | 118 | 57.61 |