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.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

关于提升电视专题节目制作质量的对策研究

在广播电视行业不断发展条件下,电视专题节目制作也受到受众高度重视。这就应提高电视专题节目制作质量,在满足广大受众日常观看要求同时,使得我国广播电视行业向着现代化方向发展。针对电视专题节目制作进行研究,首先阐述电视专题节目制作特点,之后阐述电视专题节目制作质量问题和相关提升对策。在解决电视专题节目制作问题同时,提升电视专题节目制作质量,继而彰显电视专题节目制作优势。     

雕刻技术的研制和应用

在对铝合金铸件进行X射线实时探伤时，由于采集回来的许多图像的目标物体的轮廓比较模糊，这样在评片时容易造成对铸件的误判和漏判。针对这种现象并结合这类图像噪声源多的特点，在研究常用卷积算法的基础上，采用特殊卷积（特殊的卷积核）操作，同时根据雕刻的艺术底色为灰色，最后给卷积结果加上灰度值128，实验结果表明图像中目标物体的轮廓变得更清楚，同时处理后的图像具有比较好的三维效果，这给工作人员在看图时带来了方便。     

闪光灯泵浦Nd3+:GGG激光特性研究

用闪光灯泵浦掺钕钆镓石榴石(Nd^3 ：GGG)激光晶体，研究了脉冲宽度0．5ms、1ms、1．5ms和2ms的放电泵浦下激光输出，实验获得了1．92J的最大激光能量．     

An Exploratory Study of E-Business Success Factors

E-business success factors are Important for traditional enterprises to implement e-business. This topic is attracting more and more researchers to study. This paper makes an exploratory study on the factors influencing e-business success. Firstly, based on the literature review, 52 factors are suggested. Secondly, two rounds of survey with Delphi method are conducted. Qualitative and quantitative analysis are used to identify 57 factors. This is the foundation of empirical study.     

基于WVD的防空雷达直升机信号特征分析

基于直升机目标旋转部件的调制模型，本文针对防空雷达提出了分析直升机信号特征的一种新方法——WVD法，并对直升机目标旋转部件调制回波信号在不同噪声情况下加以仿真分析，结果表明：用WVD分析雷达回波中直升机信号特征是一种非常有效的方法。     

采用8031作主控器的时域FIR数字滤波器

长期以来，ＦＩＲ数字滤波器大多是在频域上实现。因为，在时域上实现ＦＩＲ数字滤波所遇到的首要问题，是输入信号序列与冲激响应序列的卷积运算速度难以提高。然而，随着超大规模集成电路的飞速发展，硬件集成度与运算速度获得极大的改观，在时域上实现ＦＩＲ数字滤波已成为可能。ＩＭＳＡ１００是高速、高精度３２级数字信号处理器，是完成卷积运算的理想器件。本文论证了用ＩＭＳＡ１００实现时域ＦＩＲ数字滤波器的可行性和硬件设计中的一些问题，并给出了应用举例。在设计中选用８０３１单片机做主控器，大大提高了性能价格比，使这一设计具有很高的实用价值。