Abstract

Digital images are noisy due to environmental disturbances. To ensure image quality, image processing of noise reduction is a very important step before analysis or using images. Image denoising is one such powerful methodology which is deployed to remove the noise through the manipulation of the image data to produce very high quality images. In this paper, we analyzed several methods of noise removal from degraded images with Gaussian noise and salt & pepper by using adaptive wavelet threshold and compare the results in term of PSNR and MSE. After simulation can find that stein unbiased risk estimator is one of the best techniques for removing the noise from the image in terms of PSNR

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