DocumentCode :
409636
Title :
Multiscale significance run: realizing the ´most powerful´ detection in noisy images
Author :
Huo, Xiaoming ; Chen, Jihong ; Donoho, David L.
Author_Institution :
Sch. of ISyE, Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
1
fYear :
2003
fDate :
9-12 Nov. 2003
Firstpage :
321
Abstract :
Detection is a fundamental problem in many applications. In many cases, knowing the presence of underlying objects is of significant importance. Multiscale methods have been demonstrated to be advantageous in solving this problem. Besides theoretical results that have been achieved, this paper discusses how the ´most powerful´ detection can be realized, for a set of specifically organized underlying objects. We focus on the design of the detection procedure. Multiscale significance run algorithm-MSRA-serves as a general framework. It is shown that by assigning an hierarchy to the alternatives, one can nearly realize the most powerful detection under certain conditions.
Keywords :
image denoising; noise; object detection; embedded object detection; most powerful detection; multiscale significance run algorithm; noisy images; Boats; Clouds; Marine vehicles; Object detection; Organizing; Satellites; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on
Print_ISBN :
0-7803-8104-1
Type :
conf
DOI :
10.1109/ACSSC.2003.1291929
Filename :
1291929
Link To Document :
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