SURE-LET image denoising with multiple directional LOTs

This paper proposes to adopt a union of directional lapped orthogonal transforms (DirLOTs) to the SURE-LET image denoising. DirLOTs are 2-D non-separable transforms and can have directional characteristics under the fixed-critically-subsampling, overlapping, orthogonal, symmetric, real-valued and compact-support property. As a previous work, the author showed that a DirLOT overcomes a disadvantage of separable wavelet image denoising for diagonal textures and edges. Since there remains a problem that the approach is applicable only to a single geometric direction, this work further investigates to improve the performance by introducing redundant representation with multiple directions. Through some experimental results, it is verified that the proposed technique shows better performance than the traditional single wavelet approach for natural images with rich amount of geometrical structures.