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With the extensive use of sophisticated image editing software, it has become easy to manipulate digital images without any visually visible clue. Copy-move is a special type of image forgery performed by copying a part of the image and pasting anywhere else in the same image. We proposed a passive image authentication technique to determine the copy-move forgery. First, the method divides the image...
Digital image watermarking methods are one of the mostly used methods for copyright protection and image content authentication. In this article, a new bit-based reversible digital image watermarking method (BB-RIW) is proposed for authentication in images. The proposed BB-RIW method consists of identifying the pixels to be stigmatized, generating the stamp, embedding the stamp, stamping, and image...
In this paper, the problem of single-channel blind source separation (SCBSS) of a mixture of two co-frequency phase-shift keying (PSK) signals with unknown carrier frequency offsets (CFOs) is investigated. Two SCBSS algorithms which are robust to CFOs are proposed to perform separation of the mixture signals. In the first algorithm, the phase changes of the received signals caused by CFOs are tracked...
In this paper, we propose a novel point set matching algorithm to improve the matching precision in the presence of non-Gaussian noises and outliers. In our method, a non-second order similarity measure known as Kernel Mean p-Power Error (KMPE) loss is employed as the matching cost function. We introduce a local optimal solution for computing the rigid transform by repeating the correspondence estimation...
In this paper, we aim to improve the overall performance of kernel adaptive filters by adaptively combining several component filters with different parameters setting in the practical applications. The convex combination scheme is exploited to incorporate any two parallel diversity branches which could be the component filter or the output of previous combination layer. The proposed convex combination...
In this paper, a new algorithm to broaden the width of null is proposed. The algorithm is based on the property of subspace orthogonal principle between signal and noise and on virtual antenna array. Also diagonal loading technique is used to form robust beam pattern. With the theoretical analysis and computer simulations, it's shown that the superiority of proposed algorithm over other null broadening...
An important research topic of the recent years has been to understand and analyze manifold-modeled data for clustering and classification applications. Most clustering methods developed for data of non-linear and low-dimensional structure are based on local linearity assumptions. However, clustering algorithms based on locally linear representations can tolerate difficult sampling conditions only...
Common spatial patterns (CSP) is a widely used method in the field of electroencephalogram (EEG) signal processing. The goal of CSP is to find spatial filters that maximize the ratio between the variances of two classes. The conventional CSP is however sensitive to outliers because it is based on the L2-norm. Inspired by the correntropy induced metric (CIM), we propose in this work a new algorithm,...
In this paper, a new video super-resolution reconstruction (SRR) method with improved robustness to outliers is proposed. By studying the proximal point cost function representation of the R-LMS iterative equation, a better understanding of its performance is attained, which allows us to devise a new algorithm with improved robustness, while maintaining comparable quality and computational cost. Monte...
Given a corrupted low-rank matrix, robust principal component analysis performs a low-rank-plus-sparse matrix decomposition by solving a convex program. In this paper we first develop an efficient rank-revealing decomposition algorithm aided by randomization, which provides information about the singular subspaces and singular values of a given data matrix. The proposed factorization termed randomized...
A framework for reliable seperation of a low-rank subspace from grossly corrupted multi-dimensional signals is pivotal in modern signal processing applications. Current methods fall short of this separation either due to the radical simplification or the drastic transformation of data. This has motivated us to propose two new robust low-rank tensor models: Tensor Orthonormal Robust PCA (TORCPA) and...
In this paper, a robust algorithm for gait cycle segmentation is proposed based on a peak detection approach. The proposed algorithm is less influenced by noise and outliers and is capable of segmenting gait cycles from different types of gait signals recorded using different sensor systems. The presented algorithm has enhanced ability to segment gait cycles by eliminating the false peaks and interpolating...
One of the main reasons why ADS-B (Automatic Dependant Surveillance — Broadcast) has not been accepted as main source of surveillance information for Air Traffic Control (ATC) systems is its relative vulnerability against false target position reports. To remediate the issue, today's systems usually have independent surveillance system verifying the correctness of the ADS-B messages. This will make...
This paper proposes learning a linear map with local content modulation for robust content fingerprinting. The goal is to estimate a data adapted linear map that provides bounded modulation distortion and features with targeted properties. A novel problem formulation is presented that jointly addresses the fingerprint learning and the content modulation. A solution by iterative alternating algorithm...
This paper considers a multi-user multiple-input multiple-output (MU-MIMO) visible light communication (VLC) interference channel. The multi-user interference (MUI) can be successfully eliminated with the perfect knowledge of channel state information (CSI). However, the perfect information may not be available at transmitter, which will lead to severe interference and consequently degrade the system...
We study the problem of sequential binary hypothesis testing in a distributed multi-sensor network in non-Gaussian noise. To this end, we develop three robust extensions of the Consensus+Innovations Sequential Probability Ratio Test (CISPRT), namely, the Median-CISPRT, the M-CISPRT, and the Myriad-CISPRT, and validate their performance in a shift-in-mean as well as a change-in-variance test. Simulations...
An image watermarking algorithm based on grey relational analysis and singular value decomposition in wavelet domain is proposed. Firstly, the host image is processed with one-level of discrete wavelet transform. The low frequency coefficients LL1 can be obtained from mentioned operation, and LL1 is divided into non-overlapping blocks whose size is same as watermarking. Secondly, through the gained...
Ellipse fitting is widely used in computer vision and pattern recognition algorithms such as object segmentation and pupil/eye tracking. Generally, ellipse fitting is finding the best ellipse parameters that can be fitted on a set of data points, which are usually noisy and contain outliers. The algorithms of fitting the best ellipse should be both suitable for real-time applications and robust against...
Many of today's signal processing tasks consider sparse models where the number of explanatory variables exceeds the sample size. When dealing with real-world data, the presence of impulsive noise and outliers must also be accounted for. Accurate and robust parameter estimation and consistent variable selection are needed simultaneously. Recently, some popular robust methods have been adapted to such...
We study the question of reconstructing a sequence of {fi, gi}i=1s from the sum of their convolution, i.e., y = ∑i=1s fi * gi. This problem is closely related to both blind deconvolution and blind demixing problem. Our goal is to find all {fi, gi}i=1s by jointly demixing each component fi * gi and performing deconvolution procedure. While the convex program is able to solve this problem effectively...
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