No abstract

An image is often corrupted by noise in its acquisition and transmission. Image denoising is used to remove the additive noise while retaining as much as possible the important image features. The motivation is that as wavelet transform is good at energy compaction, the small coefficients are more likely due to noise and large coefficient due to important signal features [6]. The proposed technique is based upon the analysis of wavelet transform which uses a soft thresholding method for thresholding the small coefficients without affecting the significant features of the image. In the proposed work, image denoising is studied using various wavelets for different images with two different noises at various levels of decomposition and comparison is done between the e three methods of wavelet shrinkage techniques.

No abstract

No abstract

No abstract