This paper studies precision matrix estimation for multiple related Gaussian graphical models from a dataset consisting of different classes, based upon the formulation of this problem as group graphical lasso. In particular, this paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical...

This paper presents efficient methods for automatic detection and extraction of blood vessels and optic disc (OD) both of which are two prominent anatomical structures in ocular fundus images. The blood vessel extraction algorithm is composed of four steps, i.e., matched filtering, local entropy-based thresholding, length filtering, and vascular intersection detection. The OD identification inv...

In this paper we consider the problem of suppressing additive noise in video data. We propose a transformbased video denoising method in sliding, local 3D variable-sized windows. For every spatial position in each frame we use a block-matching algorithm to collect highly correlated blocks from neighboring frames and form 3D arrays for all predefined window sizes by stacking the matched blocks. ...

Thresholding based iterative algorithms have the trade-off between effectiveness and optimality. Some are effective but involving sub-matrix inversions in every step of iterations. For systems of large sizes, such algorithms can be computationally expensive and/or prohibitive. The null space tuning algorithm with hard thresholding and feedbacks (NST+HT+FB) has a mean to expedite its procedure b...

In this paper, we implement two recursive filtering and hysteresis thresholding algorithms. The first algorithm (RHT) is proposed by Monga and Deriche in [1] and the second algorithm is a recursive filtering and hysteresis multilevel hysteresis thresholding algorithm (RHMT). The algorithms are implemented on 3D images of thigh muscles. The RHT method is effective and involves fewer calculations...

To segment an image in thresholding method, a fixed threshold is not suitable if the background is rough here, we propose a new robust adaptive thresholding method using TKFCM. The method requires only one parameter to be selected and the adaptive threshold surface can be found automatically from the original image. A Robust adaptive thresholding scheme using adaptive tracking and morphological...

Thresholding method based on transition region is a new approach for image segmentation. In this paper, a novel transition region extraction and thresholding method based on maximum entropy and morphological operations. Hence, the proposed algorithm can accurately extract transition region of an image and get ideal segmentation result. The proposed algorithm was compared with maximum entropy an...

The undecimated discrete wavelet transform (UDWT) is a powerful image denoising tool, well-known to perform better than orthogonal wavelets. Unlike the case of orthogonal wavelets, noise as well as signal in the UDWT domain are non-white. Because of this inter-pixel correlation, scalar operations such as thresholding do not take full advantage of the power of UDWT. In this paper, we present a m...

This paper introduces the Extremum Consistency (EC) algorithm for avoiding local maxima and minima in a specialised domain. The most notable difference between this approach and others in the literature is that it places a greater importance on the width or consistency of an extremum than on its height or depth (amplitude). Short-term, high amplitude extrema can be encountered in many typical s...