@inproceedings{oai:niigata-u.repo.nii.ac.jp:00030883, author = {Muramatsu, Shogo and Han, Dandan and Kikuchi, Hisakazu}, book = {APSIPA ASC : Asia-Pacific Signal and Information Processing Association. Annual Summit and Conference, APSIPA ASC : Asia-Pacific Signal and Information Processing Association. Annual Summit and Conference}, month = {Oct}, note = {This paper proposes to adopt hierarchical tree construction of directional lapped orthogonal transforms (DirLOTs) to image denoising. The DirLOTs are 2-D non-separable lapped orthogonal transforms with directional characteristics. The bases are allowed to be anisotropic with the fixed-critically-subsampling, overlapping, orthogonal, symmetric, real-valued and compact-support property. As well, it is possible to introduce the trend vanishing moments (TVMs), which force wavelet filters to annihilate trend surface components. So far, the orthonormal wavelet image denoising techniques, such as the SURE-LET approach by Luisier et al., have shown a disadvantage in the restoration of diagonal textures and edges because of the separability of the adopted transforms. This work shows through some experimental results that the SURE-LET approach with DirLOTs overcomes the geometric problem.}, publisher = {APSIPA}, title = {SURE-LET Image Denoising with Directional LOTs}, volume = {2011}, year = {2011} }