
pmid: 17959472
This paper presents a fuzzy approach for contrast enhancement, based on two multi-scale transforms, namely wavelet and contourlet transforms. Separability and nondirectionality of conventional 2D wavelet transform, makes it unsuitable for sparsely representation of curve or line shaped image objects. On the other hand, the contourlet transform isa good alternative for this purpose. In this paper, coefficient enhancement, both in wavelet and contourlet spaces, is carried out by making use of simple fuzzy rules. These rules make the enhancement procedure more understandable and flexible. With this method, the knowledge and experience of the expert from the distribution of the coefficients can also be used in designing better enhancement functions. The proposed method is applied to both mentioned separable and nonseparable transforms. Implementation results demonstrate that this approach is very effective both in wavelet and contourlet spaces.
Fuzzy Logic, Image Interpretation, Computer-Assisted, Brain, Humans, Image Enhancement, Magnetic Resonance Imaging, Algorithms
Fuzzy Logic, Image Interpretation, Computer-Assisted, Brain, Humans, Image Enhancement, Magnetic Resonance Imaging, Algorithms
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