视觉信号质量评价的挑战与新进展

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this pa-per, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D im-ages/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.     

自适应噪声抵消技术在胃电信号提取中的应用

体表提取的胃电信号,在不同程度上都受到呼吸波的干扰。我们将自适应噪声抵消器(Adaptive noisecanceller)用于鉴别和消除胃电信号中的呼吸波干扰,获得了比较满意的结果。     

结合HVS和相似特征的图像质量评估方法

图像质量的客观评价方法研究在实现图像质量评价仪器化的过程中起到决定性的作用.在分析最新全参考图像质量评价算法:特征相似法(feature similarity,FSIM)的基础上,利用对比敏感度函数(contrast sensitivity function,CSF)算子以及离散余弦变换(discrete cosine transform,DCT)域的对比度掩盖效应,提出了一种改进的FSIM图像质量评价方法.该方法具有FSIM算法简单、高效等特性,同时又充分体现人眼视觉特性,更好地反映了人的主观感受.LIVE(laboratory for image and video engi-neering)测试数据集的实验结果证明,该方法在非线性回归后相关系数、斯皮尔曼相关系数、线外率等指标方面均优于传统的其他图像质量评价算法.     

体表胃电信号的自回归谱分析

在本文中,把自回归(AR)谱估计法应用于体表胃电信号的分析;而AR模型的阶次由最终预测误差(FPE)判据确定。初步的实验表明,体表胃电信号的AR谱分析结果是较为满意的。