DocumentCode :
2028653
Title :
Biased Image Correction Based on Empirical Mode Decomposition
Author :
Ogier, A. ; Dorval, T. ; Genovesio, A.
Author_Institution :
Inst. Pasteur Korea, Seoul
Volume :
1
fYear :
2007
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
The automated analysis of images is an active field of research in image processing and pattern recognition. In many applications, the first issue is to face illuminations artifacts that can appear due to bad imaging conditions. These artifacts often have direct consequences on the efficiency of the image analysis algorithms but also on the quantitative measures. This paper presents a fully automated nonuniformity correction based on empirical mode decomposition. The performances are outlined using both synthetic and real data.
Keywords :
image enhancement; image segmentation; biased image correction; empirical mode decomposition; image analysis algorithm; image processing; pattern recognition; quantitative measure; Additive white noise; Biological system modeling; Equations; Gaussian noise; Image analysis; Image processing; Interpolation; Lighting; Signal processing; Signal processing algorithms; Image analysis; biomedical image processing; biomedical microscopy; image enhancement; image restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1522-4880
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2007.4379009
Filename :
4379009
Link To Document :
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