A High-Performance Filter for Image Denoising Based on Local Features
A high-performance filter (HPF) is proposed for removing noises in corrupted images,where the local features are adopted to preserve the image local structures.Firstly,the Chebyshevs theorem and fuzzy mean process are used to adaptively estimate the detection parameters.Secondly,the local statistics theory is used to estimate noisy pixels,which is based on Radon transform.Thirdly,the PSNR is used as the evaluation metric to show the advantage of the HPF,which is compared with latest filters,such as SBF,HPFSM and the classical filter SMF.Extensive experimental results show that the HPF achieves better performances in removing any kinds of noises (impulse,Gaussian,uniform and mixed),the computational complexity of the HPF is 5 to 11 times lower than the other filters.
high-performance filter noise reduction image filter detail protection local features
Xueqing Zhao Xiaoming Wang Qiang Liu
School of Computer Science,Shaanxi Normal University,Xian,China Shaanxi Leelen Electric Power Technology Co.,LTD
国际会议
沈阳
英文
496-500
2012-09-07（万方平台首次上网日期，不代表论文的发表时间）