No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Performance evaluation of noise reduction method during on-line monitoring of MV switchgear for PD measurements by non-intrusive sensors

Partial Discharge (PD) measurement is a globally accepted method for insulation diagnosis of electrical assets. The consequences of insulation breakdown are well known. The trend is to move from conventional offline testing to online monitoring for insulation life prediction, which results in the inclusion of high frequency noise in the captured signals. Therefore de-noising is of paramount importance in online monitoring to obtain useful information from the signal.In this research, a 20 kV switchgear panel has been subjected to PD faults in the laboratory and measurements have been carried out by using different non-intrusive sensors including a novel sensor, the D-dot sensor and recorded by a high frequency oscilloscope. The measured results show the effective applicability of sensors for switchgear. The Discrete Wavelet Transform (DWT) has been used to de-noise PD signals in this paper. Time domain and frequency domain comparison of original and de-noised PD signals reveals the significance of this technique for online monitoring of Medium Voltage (MV) switchgear. Finally, an adaptive online de-noising concept, based on automatic de-noising is also proposed in this paper.     

Evaluation of orthogonal and biorthogonal wavelets for video steganography

ABSTRACT

In recent years, information security over the internet has gained enormous immersion due to a technological escalation in communication via digital media. Nowadays, videos are the most common form of media over the internet, and they have gained the attention of video steganography research community for the security of the communication. This paper implemented video steganography using a widely-known transform technique, discrete wavelet transform (DWT) which consists of different orthogonal and biorthogonal filters used for the decomposition of a frame/image. The aim of this paper is to provide a comparative evaluation for orthogonal and biorthogonal DWT filters with different matrices such as MSE, PSNR. The performance of the different filters has been evaluated both quantitatively and qualitatively to investigate the best among them. Also, the best of orthogonal and biorthogonal filters have been further evaluated with other metrics such as SSIM, BER and histogram analysis. Further, the embedding algorithm has been compared with the existing video steganography techniques. The experimental results illustrate that bior 6.8 (biorthogonal filter) outperforms the other orthogonal and biorthogonal filters in terms of visual distortion.     

Efficient implementation of chaotic image encryption in transform domains

The primary goal of this paper is security management in data image transmission and storage. Because of the increased use of images in industrial operations, it is necessary to protect the secret data of the image against unauthorized access. In this paper, we introduce a novel approach for image encryption based on employing a cyclic shift and the 2-D chaotic Baker map in different transform domains. The Integer Wavelet Transform (IWT), the Discrete Wavelet Transform (DWT), and the Discrete Cosine Transform (DCT) are exploited in the proposed encryption approach. The characteristics of the transform domains are studied and used to carry out the chaotic encryption. A comparison study between the transform-domain encryption approaches in the presence of attacks shows the superiority of encryption in the DWT domain.     

Highly efficient VLSI architecture for DWT with low-storage implementation

With the gradual increase in image resolution of the spacecraft camera, it is highly required to figure out the problem how to process a huge amount of image data on board at a high speed. As a solution, the CCSDS proposes a space-oriented image-coding standard. For the sake of high image-coding performance, it adopts wavelet transformation as a method of image data transformation. However, wavelet transformation contains multi-level data processing, which causes more computational time consumption and more memory utilization. In order to solve this problem, we propose a highly efficient VLSI architecture for DWT with low-storage. By revising the traditional lifting structure and employing time-multiplex data processing strategy to perform the second and third level of wavelet transformation by the same logic module, the usage of logic resource is reduced with no sacrifice on speed.Using a small amount of on-chip memory instead of off-chip memory to save certain parts of DWT coefficients and sending the coefficients in a specific sequence to entropy coder timely, the off-chip memory for storage of DWT coefficients is no longer required. The proposed VLSI architecture of DWT is already implemented on the Xilinx FPGA XC4VSX55, which can achieve a high performance, in terms of data throughput, reaching 95.91MPixels/s.     

小波域分存和软判决恢复的隐藏技术

研究了一种把小波变换和可视密码技术相结合的信息隐藏方案,实现对灰度图像的信息隐藏。该方案把经过Arnold变换处理后的秘密信息,按照k阶线性方程求解理论产生n幅分享图片,再把n幅分享图片应用离散小波变换信息隐藏理论,分存到n幅公开图片中。提取秘密图片时,必须要大于k幅公开图片才能获得秘密图片。实验结果表明,该方案具有很强的鲁棒性,而且秘密信息不容易丢失。     

Sensitivity and analysis GPS signals based bridge damage using GPS observations and wavelet transform

This paper uses GPS monitoring system on the Yonghe Bridge. After a year from re-construction of this bridge, cracks were pronounced 48.2 m far from the beginning of the abutment. To analyze the movements of bridge tower, the current operational safety, the cause of bridge cracks and sensitivity of GPS signals, and its movements were observed under different stress factors such as wind speed, temperature change and traffic loads. The observed lateral, longitudinal of bridge’s towers were studied. Two analytical methods namely; DWT and FT were used for the analysis of observation data. The analysis of test results indicates that: (1) The STFT is a significant step forward from the traditional FFT in terms of structural response analysis. (2) The sensitivity of GPS signals does not depend on the position of GPS antenna; and (3) the cracks of bridge deck bring out the frequency of the bridge tower movement transient characteristics.     

基于FFT与DWT联合的电力谐波检测的算法设计

目前谐波检测方法普遍存在的问题是很难对稳态谐波和非稳态谐波同时存在的信号进行准确检测.针对这种现象本文提出了一种混合算法:利用DWT将谐波信号成分低频和高频两部分;FFT对低频部分进行分析,得出稳态谐波的幅值、相位;小波熵对高频部分进行分析,得到非稳态谐波的时域信息.该算法结合以上算法的优势,完成对稳态谐波和非稳态谐波同时存在的信号的检测.并通过MATLAB验证该算法的准确性和可行性.     

一种基于DWT通道分离和函数提取的运动目标检测新方法

智能视频监控由于其智能性、实时性和高检测率成为交通和安防领域的热点研究方向,其中运动目标实时检测是智能视频监控中的一个基本和重要的部分。本文提出一种针对智能视频监控的运动目标检测新方法：包括视频帧的小波变换、YCb Cr通道分离、目标检测与融合等环节。与传统的检测方法相比,该方法检测运动目标速度较快,精确度较高,且同时还能抑制弱的阴影。     

New Optimal DWT Domain Image Watermarking Technique via Genetic Algorithm

A novel optimal image watermarking scheme is proposed in which the genetic algorithm (GA) is employed to obtain the improvement of algorithm performance. Arnold transform is utilized to obtain the scrambled watermark, and then the embedding and extractio