Shearlet-based Adaptive MMSE Estimator for Image Denoising

摘要：

An adaptive Bayesian estimator for image denoising in shearlet domain is presented, where the Bessel K Form (BKF) densities are used as the prior model of shearlet coefficients of images. The BKF densities are shown to fit very well to the observed noise-free histograms. Under this prior, a Bayesian sheartlet estimator is derived by using the minimum mean square error (MMSE) rule. Finally, a simulation is carried out to show the effectiveness of the new estimator. Experimental results show the proposed method can effectively reduce noise and remain edges, obtain better visual effect and higher PSNR.

关键词： Image denoising Bessel K Form densities Bayesian estimator Shearlet transform

作者: Wei Tian Hanwen Cao Chengzhi Deng

作者单位: Department of Information Engineering Nanchang Institute o f Technology Nanchang,China Department of Science Nanchang Institute of Technology Nanchang, China Department of Information Engineering Nanchang Institute of Technology Nanchang, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 689-692

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）