Image denoising is a challenging issue found in diverse image processing and computer vision problems. There are various existing methods investigated to denoising image. The essential characteristic of a successful model that denoising image is that it should eliminate noise as far as possible and edges preserving and necessary image information by improving visual quality. This paper presents a review of some significant work in the field of image denoising based on that the denoising methods can be roughly classified as spatial domain methods, transform domain methods, or can mix both to get the advantages of them. This work tried to focus on this mixing between using wavelet transform and the filters in spatial domain to show spatial domain. There have been numerous published algorithms, and each approach has its assumptions, advantages, and limitations depending on the various merits and noise. An analyzing study has been performed comparative in their methods to achieve the denoising algorithms, filtering approach and wavelet-based approach. Standard measurement parameters have been used to compute results in some studies to evaluate techniques while other methods applied new measurement parameters to evaluate the denoising techniques.
Digital Image Denoising Techniques in Wavelet Domain with another Filter: A review
