Multiscale significance run: Realizing the 'most powerful' detection in noisy images

Conference Record of the Asilomar Conference on Signals, Systems and Computers

Volumn 1, Issue , 2003, Pages 321-326

  Huo, Xiaoming ^a   Chen, Jihong ^a   Donoho, David L ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HIERARCHICAL STRUCTURE; MULTISCALE SIGNIFICANCE RUN ALGORITHMS (MSRA); NOISY IMAGES;

ALGORITHMS; APPROXIMATION THEORY; GEOMETRY; HIERARCHICAL SYSTEMS; OBJECT RECOGNITION; RANDOM PROCESSES;

IMAGE ANALYSIS;

EID: 4143104500     PISSN: 10586393     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. E. Arias, D. L. Donoho and X. Huo (2003). Asymptotically optimal detection of geometric objects by fast multiscale methods. Tech. Report. Stanford University. http://www-stat.stanford.edu/~donoho/reports.html.
2. E. Arias, D. L. Donoho and X. Huo (2003). Adaptive multiscale detection of filamentary structures embedded in a background of Uniform, random points. Tech. Report. Stanford University. http://www-stat.stanford.edu/~donoho/reports. html.
3. D. Donoho and X. Huo (2001). Applications of beamlets to detection and extraction of lines, curves and objects in very noisy images. Nonlinear Signal and Image Processing (NSIP), Baltimore, June.
4. D. Donoho and X. Huo (2000). Beamlet pyramids: a new form of multiresolution analysis, suited for extracting lines, curves and objects from very noisy image data. Published in Wavelet applications in signal and image processing VIII. Presented in SPIE, San Diego, CA.
5. X. Huo, J. Chen, and D.L. Donoho (2003). Multiscale Detection of Filamentary Features in Image Data. SPIE Wavelet-X, San Diego, CA, August.
6. X. Huo and D. Donoho (2002). Recovering filamentary objects in severely degraded binary images using beamlet-decorated partitioning. International Conference on Acoustic Speech and Signal Processing (ICASSP), May, Orlando, FL.