43 research outputs found
PEA265: Perceptual Assessment of Video Compression Artifacts
The most widely used video encoders share a common hybrid coding framework
that includes block-based motion estimation/compensation and block-based
transform coding. Despite their high coding efficiency, the encoded videos
often exhibit visually annoying artifacts, denoted as Perceivable Encoding
Artifacts (PEAs), which significantly degrade the visual Qualityof- Experience
(QoE) of end users. To monitor and improve visual QoE, it is crucial to develop
subjective and objective measures that can identify and quantify various types
of PEAs. In this work, we make the first attempt to build a large-scale
subjectlabelled database composed of H.265/HEVC compressed videos containing
various PEAs. The database, namely the PEA265 database, includes 4 types of
spatial PEAs (i.e. blurring, blocking, ringing and color bleeding) and 2 types
of temporal PEAs (i.e. flickering and floating). Each containing at least
60,000 image or video patches with positive and negative labels. To objectively
identify these PEAs, we train Convolutional Neural Networks (CNNs) using the
PEA265 database. It appears that state-of-theart ResNeXt is capable of
identifying each type of PEAs with high accuracy. Furthermore, we define PEA
pattern and PEA intensity measures to quantify PEA levels of compressed video
sequence. We believe that the PEA265 database and our findings will benefit the
future development of video quality assessment methods and perceptually
motivated video encoders.Comment: 10 pages,15 figures,4 table
A human-in-the-loop haptic interaction with subjective evaluation
To date, one of the challenges in Human-Computer Interaction (HCI) is fully immersive multisensory remote physical interaction technologies. The applications of haptic perception in HCI can enrich the interaction details and effectively improve the immersion and realism of interaction. In the human-in-the-loop haptic interaction system, the quality of experience (QoE) of the human operator plays an essential role. However, QoE in haptic interaction is still in its infancy. Based on the typical application scenarios of haptic operation, the paper constructs a haptic-visual interaction framework and analyzes the QoE influencing factors. Through subjective evaluation experiments, the paper establishes a haptic interaction database that can provide a research basis for further exploring the relationship between various influencing factors and interactive QoE
Efficient VVC Intra Prediction Based on Deep Feature Fusion and Probability Estimation
The ever-growing multimedia traffic has underscored the importance of
effective multimedia codecs. Among them, the up-to-date lossy video coding
standard, Versatile Video Coding (VVC), has been attracting attentions of video
coding community. However, the gain of VVC is achieved at the cost of
significant encoding complexity, which brings the need to realize fast encoder
with comparable Rate Distortion (RD) performance. In this paper, we propose to
optimize the VVC complexity at intra-frame prediction, with a two-stage
framework of deep feature fusion and probability estimation. At the first
stage, we employ the deep convolutional network to extract the spatialtemporal
neighboring coding features. Then we fuse all reference features obtained by
different convolutional kernels to determine an optimal intra coding depth. At
the second stage, we employ a probability-based model and the spatial-temporal
coherence to select the candidate partition modes within the optimal coding
depth. Finally, these selected depths and partitions are executed whilst
unnecessary computations are excluded. Experimental results on standard
database demonstrate the superiority of proposed method, especially for High
Definition (HD) and Ultra-HD (UHD) video sequences.Comment: 10 pages, 10 figure
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment
Compressed videos often exhibit visually annoying artifacts, known as
Perceivable Encoding Artifacts (PEAs), which dramatically degrade video visual
quality. Subjective and objective measures capable of identifying and
quantifying various types of PEAs are critical in improving visual quality. In
this paper, we investigate the influence of four spatial PEAs (i.e. blurring,
blocking, bleeding, and ringing) and two temporal PEAs (i.e. flickering and
floating) on video quality. For spatial artifacts, we propose a visual saliency
model with a low computational cost and higher consistency with human visual
perception. In terms of temporal artifacts, self-attention based TimeSFormer is
improved to detect temporal artifacts. Based on the six types of PEAs, a
quality metric called Saliency-Aware Spatio-Temporal Artifacts Measurement
(SSTAM) is proposed. Experimental results demonstrate that the proposed method
outperforms state-of-the-art metrics. We believe that SSTAM will be beneficial
for optimizing video coding techniques
Geometry-based spherical JND modeling for 360 display
360 videos have received widespread attention due to its realistic
and immersive experiences for users. To date, how to accurately model the user
perceptions on 360 display is still a challenging issue. In this paper,
we exploit the visual characteristics of 360 projection and display and
extend the popular just noticeable difference (JND) model to spherical JND
(SJND). First, we propose a quantitative 2D-JND model by jointly considering
spatial contrast sensitivity, luminance adaptation and texture masking effect.
In particular, our model introduces an entropy-based region classification and
utilizes different parameters for different types of regions for better
modeling performance. Second, we extend our 2D-JND model to SJND by jointly
exploiting latitude projection and field of view during 360 display.
With this operation, SJND reflects both the characteristics of human vision
system and the 360 display. Third, our SJND model is more consistent
with user perceptions during subjective test and also shows more tolerance in
distortions with fewer bit rates during 360 video compression. To
further examine the effectiveness of our SJND model, we embed it in Versatile
Video Coding (VVC) compression. Compared with the state-of-the-arts, our
SJND-VVC framework significantly reduced the bit rate with negligible loss in
visual quality
Wetting and Brazing of YIG Ceramics Using Ag–CuO–TiO2 Metal Filler
The wetting and brazing of Y3Fe5O12 (YIG) ceramics with a Ag–8CuO–2TiO2 filler was investigated for the first time. For comparison, the wettability of a Ag–10CuO filler on YIG ceramics was similarly investigated. The Ag–8CuO–2TiO2 filler has an equilibrium contact angle of approximately 31 °C on the YIG substrate at 1000 °C; thus, its wettability is excellent. Moreover, its wettability exceeds that of Ag–10CuO. The microstructure and the interfacial structure between the filler and the substrate were determined using scanning electron microscopy, X-ray diffraction, EPMA and transmission electron microscopy. The liquid Ag–8CuO–2TiO2 filler can react with the YIG substrate by forming continuous Y2Ti2O7 layers with dotted CuFe2O4 and promote the wetting behavior and bonding performance. The average shear strength could exceed 30 MPa for the joints at a brazing temperature of 1000 °C. As rupture occurred adjacent to the seam at the ceramic side, the strengths of the interfaces were characterized via nanoindentation. The hardness of the interface with doped TiO2 exceeds that of Ag–10CuO, which is strengthened by the dotted CuFe2O4 among Y2Ti2O7
Covert communication in relay and RIS networks
Covert communication aims to prevent the warden from detecting the presence of communications, i.e. with a negligible detection probability. When the distance between the transmitter and the legitimate receiver is large, large transmission power is needed, which in turn increases the detection probability. Relay is an effective technique to tackle this problem, and various relaying strategies have been proposed for long-distance covert communication in these years. In this article, we first offer a tutorial on the relaying strategies utilized in covert transmission. With the emergence of reflecting intelligent surface and its application in covert communications, we propose a hybrid relay-reflecting intelligent surface (HR-RIS)-assisted strategy to further enhance the performance of covert communications, which simultaneously improves the signal strength received at the legitimate receiver and degrades that at the warden relying on optimizing both the phase and the amplitude of the HR-RIS elements. The numerical results show that the proposed HR-RIS-assisted strategy significantly outperforms the conventional RIS-aided strategy in terms of covert rate