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