This paper introduces a new shrinkage method for image denoising. Here we calculate the probability of coefficients with the help of laplacian prior method. Thus on the basis of probability shrinkage of coefficients take place hence it is known as Probshrink. In this paper the performance of Probshrink is analysis by testing this method over some images. Here we came to know what exactly probshrink method and how it is differ form other shrinkage methods. This paper shows the Mean Square Error and PSNR value of Probshrink fr different images and finally compare it with visushrink, bayesshrink, sureshrink. This paper shows the advantages of probshrink over other shrinkage on the basis of results obtained. Here results of probshrink are shown in terms of MSE values and PSNR values. Different comparison curves of different shrinkage methods are also shown in this paper. This paper provide a complete study of Probshrink method along with its results.

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