Abstract: The Principal Component Analysis(PCA) can remove the correlation between signals,and it is easy to distinguish the signal and noise.Before the processing of target pixel block,first of all,we should find the training samples in a certain local pixel search domain which are similar to the target pixel block.In this paper,we get the copy of the image,and use the Bivariate shrinkage denoising method(Bishrink) to manage it.After that,we use Euclidean distance of the corresponding pixel block to replace the similarity between the target pixel block and the local pixel block,which will reduce the effect of the noise,and play an important role in the follow-up PCA transformation.Simulation results show that,improved LPG-PCA method has the very big enhancement in the quality of the image compared with the method before improvement.

Key words: Image denoising,Local pixel grouping,Principal component analysis,Bivariate shrinkage denoising method