X-ray image enhancement based on fuzzy sure entropy in LabVIEW

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 inv...

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Bibliographic Details
Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 395 - 398
Main Authors Ce Li, Yannan Zhou, Chengsu Ouyang, Lihua Tian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Fuzzy set theory
Image enhencement
LabVIEW
Shannon entropy
X-ray image
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Summary: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.
ISBN:9781467311830
1467311839
DOI:10.1109/BMEI.2012.6513007