Fusion of noisy images based statistical model in shearlet domain

摘要：

A new image fusion approach based on the modeling of shearlet coefficients with normal inverse gaussian model is proposed. The approach focus on the fusion of noisy images. Based on the statistical model and additive white gaussian noise, an subband adaptive shrinkage function is derived by using the maximum a posteriori rule. And then, the new scheme for shearlet-domain image fusion is proposed by incorporating the adaptive shrinkage rule into the fusion scheme. Experimental results show the proposed method perfor very well with noisy images, outperform other conventional methods.

关键词： Image fusion statistical model denoising maximum a posteriori

作者: Chengzhi Deng Xin Hu

作者单位: School of Information Engineering, Nanchang Institute of Technology, Nanchang China Key Laboratory of Optic-electronic and Communication, Jiangxi Science and Technology Normal Universi

会议类型: 国际会议

会议名称: 第七届多光谱图象处理与模式识别国际学术会议

会议地点: 桂林

会议语种:英文

页码: 1-6

在线出版日期: 2011-11-01（万方平台首次上网日期，不代表论文的发表时间）