Article ID Journal Published Year Pages File Type
4948203 Neurocomputing 2016 16 Pages PDF
Abstract
Image enhancement is a very significant issue in image processing and analysis. In practice, many images (e.g.images captured from X-ray systems) are of low quality, such a slow-luminance and low-contrast, which must be enhanced before further processing. Fuzzy set theory is a useful tool for handling the ambiguity or uncertainty. Many researchers use the maximum Shannon entropy and fuzzy complement for image enhancement. But these methods are easy to be over-enhanced or under-enhanced or time-consuming. In this paper, a flexible method is proposed, which utilizes the maximum fuzzy Sure entropy, fuzzy c-partition and fuzzy complement (MSRM). Furthermore, a positive threshold value selection algorithm is developed to tune the enhancement performance of the proposed method. A variety of highly degraded images have been experimented by the proposed method. The comparisons of those experimental results show that the performance of our method overwhelms those of the existing ones.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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