Affiliations: [a] Computer and Information Institute, Shaanxi Institute of Technology, Xi’an, China
| [b] School of Economic Management, Shaanxi Institute of Technology, Xi’an, China
| [c]
Syracuse University, Center for Policy Research, Eggers Hall, Syracuse, NY, USA
Correspondence:
[*]
Corresponding author. Bo Wanga, Computer and Information Institute, Shaanxi Institute of Technology, Xi’an
710302, China. E-mail: Xli0630@163.com.
Abstract: Due to the poor image quality and complex enhancement process in the current image contrast fuzzy enhancement algorithm, a multilevel image contrast fuzzy enhancement algorithm in multimedia network based on homogeneity measurement was put forward. This algorithm used the minimum fuzzy entropy to detect noise in multilevel image and remove noise through improved Shannon entropy, so as to achieve restoration of multilevel image. According to the membership degree of restored image, the local feature of image was determined to realize and the homogeneity expression of image. Then, the nonlinear transformation was introduced to optimize the image homogeneity. Thus, the multilevel image contrast fuzzy enhancement in multimedia network was realized. Experimental results show that the proposed algorithm can effectively guarantee the image quality after the contrast enhancement and reduce the computational complexity.
