In this paper, we use non-subsampled shearlet transform (NSST) and Krawtchouk Moment Invariants (KMI) to realize image retrieval based on texture and shape features. Shearlet is a new sparse representation tool of multidimensional function, which provides a simple and efficient mathematical framework. We decompose the images by NSST. The directional subband coefficients are modeled by Generaliz...

The only quadrature operator of order two on L2(R) which covaries with orthogonal transforms, in particular rotations is (up to the sign) the Riesz transform. This property was used for the construction of monogenic wavelets and curvelets. Recently, shearlets were applied for various signal processing tasks. Unfortunately, the Riesz transform does not correspond with the shear operation. In thi...

We propose an algorithmic framework based on ADMM/split Bregman that combines a multilevel adapted, iterative reweighting strategy and a second total generalized variation regularizer. The level adapted reweighting strategy is a combination of reweighted `-minimization and additional compensation factors for a uniform treatment of the sparsity structure across all levels. Classical multilscale ...

The analysis and detection of edges and interface boundaries is a fundamental problem in applied mathematics and image processing. In the study of the wave equation, for example, one is interested in the evolution of moving fronts; in image processing and computer vision, the detection and analysis of edges is an essential task for applications such as shape recognition, image enhancement and c...