In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transf...
This paper suggests a discriminative approach for wavelet denoising
where a set of mapping functions (MF) are applied to the transform
coefficients in an attempt to produce a noi...
The contourlet transform was proposed as a directional multiresolution image representation that can efficiently capture and represent singularities along smooth object boundaries...
Coupling the periodic time-invariance of the wavelet transform with the view of thresholding as a projection yields a simple, recursive, wavelet-based technique for denoising sign...
Alyson K. Fletcher, Vivek K. Goyal, Kannan Ramchan...
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...