DocumentCode
2426813
Title
Advanced Image Processing Techniques for Maximum Information Recovery
Author
Luo, Jiecai ; Cross, James
Author_Institution
Dept. of Electr. Eng., Southern Univ., Baton Rouge, LA
fYear
2007
fDate
4-6 March 2007
Firstpage
58
Lastpage
62
Abstract
Some radio frequency and optical sensors collect large-scale sets of spatial imagery data whose content is often obscured by fog, clouds, foliage and other intervening structures. Often, the obstruction is such as to render unreliable the definition of underling images. There are several typical mathematical methods used in image processing to remove interferences from images to include spectral methods, wave front or shock methods, and the use of non-abelian group operations. In this paper, a new advanced image processing technique based on image segmentations has been developed and tested for the removal of fog, clouds, foliage and other interfering structures. The developed method has been applied to certain images to demonstrate its effectiveness in removing unwanted sub-images.
Keywords
blind source separation; image segmentation; pattern clustering; K-means clustering; cloud removal; fog removal; foliage removal; image processing techniques; image segmentation; information recovery; interference removal; optical sensors; radio frequency sensors; spatial imagery data; Clouds; Electric shock; Image processing; Image segmentation; Interference; Large-scale systems; Optical sensors; Radio frequency; Rendering (computer graphics); Testing; Image segmentation; K-means clustering; Nonlinear processing;
fLanguage
English
Publisher
ieee
Conference_Titel
System Theory, 2007. SSST '07. Thirty-Ninth Southeastern Symposium on
Conference_Location
Macon, GA
ISSN
0094-2898
Print_ISBN
1-4244-1126-2
Electronic_ISBN
0094-2898
Type
conf
DOI
10.1109/SSST.2007.352317
Filename
4160803
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