Low-SNR Image Noise Removal Based on Local Edge-preserving Function
Ran Liu · Journal of Sichuan University · 2009
Traditional noise removal arithmetic required that the signal-noise-ratio of the image was high,and the noise removed image by the traditional noise removal arithmetic lost large amounts of edge and texture information in the image.In order to overcome these problems,a novel procedure for the low signal-noise-ratio(SNR) image noise removal based on the local edge-preserving function was proposed,which made up the limitation of the traditional methods.Firstly,adaptive median filter was used to remove the part of salt-and-pepper noise and to preserve the edge and texture information in the image.Secondly,local edge-preserving function was built on the basis of analyzing the relation of pixels in the local image block.Lastly,a minimization problem was solved by the Poly-Ribiere-Polak(PRP) method in order to remove the Gaussian noise and the remnant salt-and-pepper noise in the image.Comparison of the results showed that the noise removal efficient of the present method was better,especially when the PSNR of the image was 5.4 dB,the PSNR of the result image was 24.3 dB.