one of the challenging issues in managing the existing large digital image libraries and databases is content based image retrieval (cbir). the accuracy of image retrieval methods in cbir is subject to effective extraction of image features such as color, texture, and shape. in this paper, we propose a new image retrieval method using contourlet transform coefficients to index texture of the im...

In this paper we introduce and analyze a set of regularization expressions based on self-similarity properties of images in order to address the classical inverse problem of image denoising and the ill-posed inverse problem of single-frame image zooming. The regularization expressions introduced are constructed using either the fractal image transform or the newly developed “Nonlocal-means (NL-...

Obtaining diffusion coefficients from PFG NMR diffusion (a.k.a DOSY) data is, in the general case, an ill-posed problem. Numerous methods for processing such data have therefore been developed, each with different constraints and assumptions. The Regularized Resolvent Transform (RRT) is a proven and robust method for spectral inversion. In earlier papers RRT, albeit very slow, was argued to be ...

In this paper, a Bregman iteration based total variation image restoration algorithm is proposed. Based on the Bregman iteration, the algorithm splits the original total variation problem into sub-problems that are easy to solve. Moreover, non-local regularization is introduced into the proposed algorithm, and a method to choose the non-local filter parameter locally and adaptively is proposed....

This paper addresses the issue of robust filtering for time varying uncertain discrete time systems. The proposed robust filters are based on a regularized least-squares formulation and guarantee minimum state error variances. Simulation results indicate their superior performance over other robust filter designs. keywords: regularization, least-squares, robust filter, regularization parameter,...

We discuss the problem of image restoration from observed images. Most of the image restoration filters proposed so far include parameters that control the restoration properties. For bringing out the optimal restoration performance of the filters, the parameter values should be determined so as to minimize a certain error measure such as the mean squared error (MSE) between the restored image ...

Several methods of combining a number of time series into a single series are discussed. They are all individual filtering followed by summation and are somewhat like Wiener filtering in that a least squares criterion is used to define the filter coefficients. They differ from Wiener filtering in that signal information is given in the form of various linear constraints on the filter coefficien...

Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (...