DocumentCode :
2133609
Title :
X-ray image enhancement based on fuzzy sure entropy in LabVIEW
Author :
Ce Li ; Yannan Zhou ; Chengsu Ouyang ; Lihua Tian
Author_Institution :
Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Tech, Lanzhou, China
fYear :
2012
fDate :
16-18 Oct. 2012
Firstpage :
395
Lastpage :
398
Abstract :
Image enhancement is an important problem in image processing and image analysis, especially for low quality X-ray images with both low-illumination and low-contrast. This paper proposes a novel X-ray image enhancement method, which utilizes the maximum fuzzy sure entropy, fuzzy c-partition, and involutive fuzzy complements. In our proposed method, an image is partitioned into dark part and bright part by fuzzy c-partition and the involutive fuzzy complements are obtained, then the exhausted search approach is used to attain the optimal pair and based on the maximum fuzzy sure entropy. In a LabVIEW system platform, many X-ray images have been experimented by the proposed method, and the comparisons of those experimental results show that the proposed scheme has better performance over the traditional algorithms.
Keywords :
X-ray imaging; entropy; fuzzy set theory; image enhancement; medical image processing; LabVIEW; X-ray image enhancement; fuzzy c-partition; image analysis; involutive fuzzy complements; low quality X-ray images; low-contrast; low-illumination; maximum fuzzy sure entropy; Fuzzy set theory; Image enhencement; LabVIEW; Shannon entropy; X-ray image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-1183-0
Type :
conf
DOI :
10.1109/BMEI.2012.6513007
Filename :
6513007
Link To Document :
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