A Novel Approach for Reduction of Poisson Noise in Digital Images

ABSTACT An image is often corrupted by noise in its acquisition and transmission by various kinds of noises. Image denoising using thresholding methods means find appropriate value (threshold)which separates noise values to actual image values without affecting the significant features of the image.Wavelet transform represents image energy in compact form and representation helps in determining threshold between noisy features and important image feature. This paper is organized as follows: First poison noise is removed by median filter; and then removed by wiener filter, second noisy image is denoised with the help of wavelet based techniques using thresholding, third thresholding is applied on the result of first and second simultaneously for image denoising and fourth PSNR (Peak Signal To Noise Ratio), MSE (Mean Square Error) calculated and results are compared in all cases. The aim of this paper is to identify the best poison noise removal filter from the comparative study analysis of filtering methods and wavelet based thresholding technique. The best filter is estimated by calculating Peak Signal Noise Ratio (PSNR) and Means Square Error (MSE).