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Proceedings Paper

Wavelets for detection and enhancement of silver grains in in-situ hybridization
Author(s): Haojun Wang; Chongxun Zheng; Xiangguo Yan
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Paper Abstract

In this paper, a novel multi-scale method is proposed to detect silver grains including more subtle ones in in-site hybridization. The multi-scale representation is built using an undecimated discrete wavelet transform, a biorthogonal B- spline wavelet basis is applied to the transform. A multi- scale and orthogonal feature set can be acquired from the wavelet decomposition as input to a multilayer feed-forward neural network which maximizes the separation between the presence and absence of grains. The resulting map of the classification indicates the presence and location of silver grains. We use it to restrict enhancement to highly localized regions identified by the detection algorithm. Then an inverse wavelet transform is applied to reconstruct the detected and enhanced objects. Experiment results show that the proposed approach is able to highlight silver grains while significantly reducing the contrast of the remaining image.

Paper Details

Date Published: 18 September 2001
PDF: 6 pages
Proc. SPIE 4556, Data Mining and Applications, (18 September 2001); doi: 10.1117/12.440283
Show Author Affiliations
Haojun Wang, Xi'an Jiao Tong Univ. (China)
Chongxun Zheng, Xi'an Jiao Tong Univ. (China)
Xiangguo Yan, Xi'an Jiao Tong Univ. (China)

Published in SPIE Proceedings Vol. 4556:
Data Mining and Applications
Deren Li; Jie Yang; Jufu Feng; Shen Wei, Editor(s)

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