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) |
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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