Glaucoma is a neurodegenerative illness and is considered as a standout amongst the most
widely recognized reasons for visual impairment. Nerve's degeneration is an irretrievable …

This paper proposes a deep image analysis–based model for glaucoma diagnosis that uses
several features to detect the formation of glaucoma in retinal fundus. These features are …

This paper studies the performances of different ship detectors based on adaptive threshold
algorithms. The detection algorithms are based on various clutter distributions and assessed …

In many applications, d-dimensional observations result from the random presence or
absence of random signals in independent and additive white Gaussian noise. An estimate …

We propose a novel method for noise power spectrum estimation in speech enhancement.
This method called extended-DATE (E-DATE) extends the d-dimensional amplitude trimmed …

This work addresses the unification of some basic functions and thresholds used in non-
parametric estimation of signals by shrinkage in the wavelet domain. The soft and hard …

We address the problem of blind source separation in the underdetermined mixture case.
Two statistical tests are proposed to reduce the number of empirical parameters involved in …

Wave atom transform is a new multi-resolution technique, which has the ability to adapt to
arbitrary local directions of a pattern, and to sparsely represent anisotropic patterns aligned …

Based on recent results that link sparsity hypotheses and robust statistics, a new noise
variance estimator for application to communication electronic support (CES) is derived in …

Wavelet transforms are said to be sparse in that they represent smooth and piecewise
regular signals by coefficients that are mostly small except for a few that are significantly …