Step wise Ratio GM(1,1) Model for Image Denoising

摘要：

To reduce image noise, we propose a novel image filter based on stepwise ratio grey model (SGM).The basic theory and the method of stepwise ratio grey prediction model are introduced first.The new filter makes use of neighborhoods around each noisy pixel to predict its intensity value and reflects the dynamics of stepwise ratio.The experimental results show that the proposed method, compared with the median filter and GM(1,I) model, improves the effect of the removal of impulse noise, such as salt & pepper noise.The improved algorithm can effectively eliminate image noise, preserve the images details and edges, increase SNR(signal-to-noise ratio) as well as PSNR (peak signal-to-noise ratio), reduce MSE(mean square error) and MAE(mean absolute error), and significantly improve the images visual effect.Therefore the proposed method is practicable.

关键词： Dynamics stepwise ratio GM(1,1) model PSNR MSE

作者: ZHAO Jin-shuai YANG Su-jin LIU Xin YANG Bao-hua

作者单位: Department of Computer Science Zhoukou Normal University Zhoukou,China School of Management Xuzhou Normal University Xuzhou,China

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Grey System and Intelligent Services Joint with the 15th WOSC International Congress on Cybernetics and System(2011 IEEE灰色系统与智能服务国际会议暨系统与控制世界组织第15届年会)

会议地点: 南京

会议语种:英文

页码: 670-674

在线出版日期: 2011-09-15（万方平台首次上网日期，不代表论文的发表时间）