In this article we consider estimation of sparse covariance matrices and propose a thresholding procedure that is adaptive to the variability of individual entries. The estimators are fully data-driven and demonstrate excellent performance both theoretically and numerically. It is shown that the estimators adaptively achieve the optimal rate of convergence over a large class of sparse covarianc...

Two algorithms for document image thresholding are presented, that are suitable for scanning document images at high-speed. They are designed to operate on a portion of the image while scanning the document, thus, they fit a pipeline architecture and lend themselves to real-time implementation. The first algorithm is based on adaptive thresholding and uses local edge information to switch betwe...

ultrasound images suffer of multiplicative noise named speckle. different de-speckling algorithms run either in spatial domain or in transformed domain. in this paper, an adaptive filter in spatial domain according to assume the nakagami distribution as the statistic of log-compressed ultrasound images is used. for de-speckling in transformed domain, the non-sub sampled shearlet transform is us...

in recent years, based on the growing importance of clean energy in comparison with conventional energy production from fossil fuels, dg systems are gradually becoming more popular all over the world. these resources solve many problem of system. however, these resources create some other problems too. one of the most problem of dgs is unwanted islanding. this paper addresses reliable passive i...

The main disadvantage of traditional global thresholding techniques is that they do not have an ability to exploit information of the characteristics of target images that they threshold. In this paper, we propose a hybrid thresholding method that combines the P-tile method with an edge detector to assist it in the thresholding process. This method successfully generates more accurate object sh...

Image thresholding is a challenging task in image processing field. Many efforts have already been made to propose universal, robust methods to handle a wide range of images. This paper introduces a new optimization-based thresholding approach. The optimizer, Differential Evolution (DE) algorithm, minimizes dissimilarity between the input grey-level image and the bi-level (thresholded) image. T...

After highlighting vessel like structure by an appropriate filter in Matched Filter (MF) technique, thresholding strategy is needed for the automated detection of blood vessels in retinal images. For the purpose, we propose to use a new technique of entropic thresholding based on Gray Level Spatial Correlation (GLSC) histogram which takes into account the image local property. Results obtained ...

Most thresholding algorithms have difficulties processing images with unimodal distributions. In this paper an algorithm, based on finding a corner in the histogram plot, is proposed that is capable of performing bilevel thresholding of such images. Its effectiveness is demonstrated on synthetic data as well as a variety of real data, showing its successful application to edges, corners, differ...

the aim of this paper is to improve the performance of the conventional goertzel algorithm in determining the protein codingregions in deoxyribonucleic acid (dna) sequences. first, the symbolic dna sequences are converted into numerical signals usingelectron ion interaction potential method. then by combining the modified anti-notch filter and linear predictive coding model,we proposed an effic...