Selective Parameters Based Image Denoising Method

In this paper, we propose a Selective Parameters based Image Denoising method that uses a shrinkage parameter for each coefficient in the subband at the corresponding decomposition level. Image decomposition is done using the wavelet transform. VisuShrink, Sure Shrink, and BayesShrink define good thresholds for removing the noise from an image. Sure Shrink and BayesShrink denoising methods depend on subband to evaluate the threshold value whereas the VisuShrink is a global thresholding method. These methods remove too many coefficients and do not provide good visual quality of the image. Our proposed method not only keeps more noiseless coefficients but also modifies the noisy coefficients using the threshold value. We experimentally show that our method provides better performance in terms of objective and subjective criteria i.e. visual quality of image than the VisuShrink, Sure Shrink, and BayesShrink.