| Summary: | 碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 97 === A multi-methodology evolutionary computation and fuzzy similarity measure based hybrid image filter for color image restoration is proposed in this thesis. First, a multi-methodology evolutionary computation (MMEC) is proposed for multi-objective optimization problems. Then, a hybrid image filter with fuzzy-based similarity measure is proposed for noise reduction. Finally, an experience-based construction of fuzzy sets in the similarity measure has been shown as near-optimized via MMEC and is applied to color image restoration. The experimental results show that the proposed fuzzy similarity measure based hybrid image filter can achieve better filtering quality than the classical vector filters and the bilateral filter which are restricted by the shapes of functions themselves. The proposed filter is effective to restore color images contaminated by impulse noise, Gaussian noise, and mixed noise.
|
|---|
