Showing papers in "Signal Processing in 2021"

TL;DR: Wang et al. as discussed by the authors proposed a new visually secure image encryption scheme using adaptive-thresholding sparsification to greatly improve the quality of the reconstructed image and designed a new parallel CS technique to tremendously improve the processing efficiency.

TL;DR: A detailed literature panorama of medical image fusion is presented in this paper, where pixel-level, feature-level and decision-level fusion methods are highlighted and discussed with several approaches in each category Theories behind fusion algorithms are explored aiming to address challenges and limitations of each classes.

TL;DR: In this paper, a coupling chaotic system based on a certain unit transform is introduced, which can combine any two 1D chaotic maps to generate a new one with better performance in cryptography applications.

TL;DR: The development of the linear active noise control (ANC) technique in the past decade was reviewed, with recent advances of NLANC algorithms, such as spline ANC algorithms, kernel adaptive filters, and nonlinear distributed ANC algorithms.

TL;DR: In this paper, a color image cryptosystem based on improved genetic algorithm and matrix semi-tensor product (STP) is introduced, which is composed of five stages, preprocessing, DNA encoding, crossover, mutation and DNA decoding.

TL;DR: The qualitative and quantitative experimental results demonstrate the advantage of the proposed fusion method in terms of the visual quality and fusion performance.

TL;DR: In this article, the authors provide a didactic treatment of the emerging topic of signal processing on higher-order networks, with a special emphasis on the concepts needed for the processing of signals supported on these structures.

TL;DR: A novel subspace algorithm is derived, which offers closed-form solution to 2D-DOD and2D-DOA estimation and is insensitive to the sensor position error.

TL;DR: A method that leverages depth information in clear shapes to detect the boundary of salient objects and its substantial improvement over state-of-the-art methods for RGB-D salient object detection on four representative datasets is proposed.

TL;DR: A multi-scale decomposition fusion method based on saliency, which uses a fusion rule based on phase congruency for fusion of detail layers so that the details could be retained better than the traditional “max-absolute” fusion rule.

TL;DR: In this paper, a tensor subspace low-rank learning method with a non-local prior was proposed to exploit the low rankness of both spatial and spectral modes of an HSI tensor.

TL;DR: Experimental results show that the marked medical images generate by the proposed RDHACEM algorithm have better visual quality and larger embedding capacity in the ROI than those generated by the up-to-date RDH methods.

TL;DR: In this article, a hardware realizable neuro-dynamic model based on augmented Lagrangian and projection theorem is proposed to solve the resultant nonconvex optimization problem with inequality constraints.

TL;DR: In this article, a novel image encryption and adaptive embedding algorithm is proposed by combining 4D memristive hyperchaos, parallel compressive sensing (PCS) and slant transform (ST).

TL;DR: A novel multi-focus image fusion method which can effectively bridge the gap between the transform domain and spatial domain based methods is proposed, which outperforms some state-of-the-art methods in both quantitative and qualitative evaluations.

TL;DR: The cost functions used in these algorithms have been summarized and a timeline of algorithm development in this area has been added to provide an excellent overview on the topic.

TL;DR: This work extends the exact thumbnail preserving image encryption (TPE) scheme to propose a three-pixel exact TPE scheme, called TPE2, and shows that the image encrypted by the scheme has a good image quality and a satisfactory balance usability and privacy.

TL;DR: In this paper, a 2-dimensional convolutional neural network (2-D CNN) was proposed for autoregressive (AR) and ARMA time series modeling based on ImageNet classifications with a 2D CNN.

TL;DR: In this paper, a new variant of SSA called Circulant SSA (CiSSA) is proposed, which allows to extract the signal associated to any frequency specified beforehand.

TL;DR: This paper proposes a robust adaptive beamforming (RAB) algorithm based on a novel method for estimating the steering vectors (SVs), which is robust against various types of mismatch and is superior to other existing reconstruction-based beamforming algorithms.

TL;DR: A robust blind watermarking scheme based on quaternion QR decomposition (QQRD) for color image copyright protection, while using algebraic structure-preserving method to release its computational complexity.

TL;DR: Compared with the existing analysis on the IWF-SSAF algorithm, the proposed analysis does not require the assumptions of large number of subbands, long adaptive filter, and paraunitary analysis filter bank, and matches well the simulated results.

TL;DR: In this paper, a deep RL based anti-jamming strategy design method is proposed in which a transmit/receive time-sharing jammer may adopt multiple different jamming strategies, and a specialized strategy learning algorithm that treats probability of detection as the reward signal and uses proximal policy optimization to solve the RL problem of the radar and the jammer.

TL;DR: A new S-box generator based on isomorphic ordered elliptic curves that satisfies conditions (i)-(iv) and can generate a highly secure ciphertext for a plain text with a high correlation is proposed.

TL;DR: A robust algorithm to solve the problem of instability in numerical calculation based on the minimum error entropy criterion is proposed and a method to estimate the steady-state errors is proposed.

TL;DR: Experimental results show that proposed Riesz fractional derivative in Fractional Fourier Transform domain outperforms the existing techniques by providing improvement in various performance parameters.

TL;DR: A novel discrete orthogonal transformation called the separable Charlier-Krawtchouk transformation of fractional order (FrCKTs) is presented and a new technique for the zero watermarking of bio-signals for the protection of intellectual property rights is proposed.

TL;DR: Experimental results show that the proposed algorithm effectively removes haze and outperforms the several dehazing methods based on quantitative and qualitative evaluations.

TL;DR: The proposed reduced-complexity algorithm is very effective in (even severe) multipath conditions, outperforming natural competitors also when the number of antennas and samples is kept at the theoretical minimum, and exhibiting robustness to several types of mismatch.

TL;DR: In this paper, an adaptive energy-constrained VMD method based on spectrum segmentation was proposed for rolling bearing fault detection. But the performance of the VMD algorithm is highly dependent on the input parameters: the number of modes, the penalty parameter and even the initial center frequency (ICF).