Abstract
Several multiscale objective functions for the direct segmentation of tomographic images are presented. Standard methods of signal detection and estimation are used to develop a theoretical performance analysis, which quantitatively predicts the performance at realistic noise levels. The analysis compares the relative merit of multiscale and monoscale segmentation, and shows the impact of the Shepp-Logan skull's quantization error.
| Original language | English (US) |
|---|---|
| Article number | 413555 |
| Pages (from-to) | 177-181 |
| Number of pages | 5 |
| Journal | Proceedings - International Conference on Image Processing, ICIP |
| Volume | 2 |
| DOIs | |
| State | Published - 1994 |
| Event | The 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA Duration: Nov 13 1994 → Nov 16 1994 |
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
- Signal Processing