Efficient bivariate image denoising technique using new orthogonal CWT filter design. Issue 8 (1st August 2018)

• Record Type: Journal Article
• Authors: Fahmy, Mamdouh F.; Fahmy, Omar M.
• Is Part Of: IET image processing. Volume 12:Issue 8(2018)
• Page Start: 1354
• Page End: 1360
• Publication Date: 2018-08-01
• Subjects: wavelet transforms -- filtering theory -- image denoising; efficient bivariate image denoising technique -- orthogonal CWT filter design -- complex wavelet transforms -- shift invariant features -- perfect reconstruction feature -- CWT system -- CWT Hilbert constraints -- bivariate thresholding -- noisy CWT coefficients -- children -- parent wavelet coefficient; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2017.1117
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : The complex wavelet transforms (CWTs) are known for their excellent edge preserving together with nearly shift invariant features. This study presents new orthogonal CWT filter designs. The proposed designs guarantee the perfect reconstruction feature of the CWT system while satisfying in a least squares sense, the CWT Hilbert constraints over the filter's pass‐band. The study also describes a new image denoising technique based on bivariate thresholding of the noisy CWT coefficients. In this respect, a simple model is proposed to model the dependence between the magnitudes of the children and parent wavelet coefficient at every sub‐band. This allows the derivation of a closed‐form expression for the clean thresholded magnitudes. Several illustrative examples are given to verify the superior denoising performance especially in salt & pepper case.