Biomedical Engineering Reference
In-Depth Information
[79] Wang, J., Li, J., Gray, R., and Wiederhold, G., Unsupervised multires-
olution segmentation for images with low depth of field, IEEE Trans.
Pattern Anal. Mach. Intell., Vol. 23, No. 1, pp. 85-90, 2001.
[80] Etemad, K., Doermann, D., and Chellappa, R., Multi-scale segmentation
of unstructured document pages using soft decision integration, IEEE
Trans. Pattern Anal. Mach. Intell., Vol. 19, No. 1, pp. 92-96, 1997.
[81] Porter, R. and Canagarajah, N., A robust automatic clustering scheme
for image segmentation using wavelets, IEEE Trans. Image Process.,
Vol. 5, No. 4, pp. 662-665, 1996.
[82] Zhang, J., Wang, D., and Tran, Q., A wavelet-based multiresolution
statistical model for texture, IEEE Trans. Image Process., Vol. 7, No.
11, pp. 1621-1627, 1998.
[83] Choi, H. and Baraniuk, R., Multis-cale image segmentation using
wavelet-domain hidden markov models, IEEE Trans. Image Process.,
Vol. 10, No. 9, pp. 1309-1321, 2001.
[84] Li, J. and Gray, R., Context-based multi-scale classification of docu-
ment images using wavelet coefficient distributions, IEEE Trans. Im-
age Process., Vol. 9, No. 9, pp. 1604-1616, 2000.
[85] Charalampidis, D. and Kasparis, T., Wavelet-based rotational invariant
roughness features for texture classification and segmentation, IEEE
Trans. Image Process., Vol. 11, No. 8, pp. 825-837, 2002.
[86] Chan, T. F. and Vese, L. A., Active controus without edges, IEEE Trans.
Image Process., Vol. 10, No. 2, pp. 266-277, 2001.
[87] Yezzi, A., Tsai, A., and Willsky, A., A statistical approach to image seg-
mentation for biomodal and trimodal imagery, ICCV, pp. 898-903, 1999.
[88] Canny, J., A computational approach to edge detection, IEEE Trans.
Pattern Anal. Mach. Intell., Vol. 8, No. 6, pp. 679-698, 1986.
[89] Aydin, T., Yemez, Y., Anarim, E., and Sankur, B., Multi-directional and
multi-scale edge detection via M-band wavelet Transform, IEEE Trans.
Image Process., Vol. 5, No. 9, pp. 1370-1377, 1996.
