DocumentCode :
2750375
Title :
A blind system to identify and filter degradations affecting an image
Author :
Chehdi, Kacem ; Vozel, Benoît ; Carton-Vandecandelaere, Marie-Paule ; Kermad, Chafik
Author_Institution :
Rennes I Univ., France
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
1987
Abstract :
For a high quality analysis and therefore a good pattern recognition, it is necessary to process degraded images. An image can be underexposed and degraded by noise or blur or a combination of them, or bright and degraded by noise or blur or a combination of them. The existing processing methods suppose that the nature of the degradations and some of the statistics are known. In this paper we propose a blind automatic procedure to (i) identify the nature of the degradation affecting an image and (ii) enhance and/or filter the images selected as dark and/or altered by a preponderant noise. The identification procedure is made of a sequence of three classifications, run by the non-parametric CHAVL algorithm, on different sets of statistics computed from the observed image. Considering the filtering aspect we propose a new method to estimate the standard deviation of the noise from histograms computed on homogeneous regions of any shape
Keywords :
Wiener filters; image classification; image enhancement; image restoration; statistical analysis; blind automatic procedure; blind system; blur; classifications; degradations; degraded images; histograms; homogeneous regions; identification procedure; noise; nonparametric CHAVL algorithm; preponderant noise; statistics; Degradation; Filtering; Filters; Histograms; Image analysis; Noise shaping; Pattern analysis; Pattern recognition; Shape; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-5747-7
Type :
conf
DOI :
10.1109/ICOSP.2000.893496
Filename :
893496
Link To Document :
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