DocumentCode :
2035823
Title :
Non-Stationarity Detection in Natural Images
Author :
Raj, Raghu G. ; Bovik, Alan C. ; Geisler, Wilson S.
Author_Institution :
Texas Univ. Austin, Austin
Volume :
3
fYear :
2007
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
We present a novel approach for non-stationarity detection in natural images by exploiting the prior knowledge of the independent component structure of scene statistics. Our proposed non-stationarity index is conceptually simple and is intertwined with the probabilistic structure of the image segment being analyzed. It shows consistently good results when applied to natural scenes and, we expect, will find useful applications in computer vision algorithms in as much as the detection of statistically non-stationary locations in images can be an important preliminary step toward the understanding of scene content and in the guiding of visual fixations.
Keywords :
image segmentation; natural scenes; object detection; probability; statistical analysis; computer vision; fixation selection; image segmentation; natural image; natural scenes; nonstationarity image detection; probabilistic structure; scene statistics; Application software; Clouds; Computer vision; Image analysis; Image segmentation; Image texture analysis; Independent component analysis; Layout; Machine vision; Statistics; Fixation selection; ICA; Natural Scene Statistics; Non-stationarity; Textures; Vision Systems;
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.2007.4379307
Filename :
4379307
Link To Document :
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