Study of No-Reference Video Quality Metrics for HEVC Compression, Journal of Telecommunications and Information Technology, 2016, nr 1

The paper proposes a No-Reference (NR) quality assessment measurement originally developed for H.264, used for High Efficiency Video Coding (HEVC). In particular, authors present an investigation of NR metrics to objectively estimate the perceptual quality of a set of processed video sequences. The authors take into account typical distortions introduced by the block-based coding approaches like HEVC codec. The underlying processing used for the quality assessment considers the blockiness caused by the boundaries of each coded block and the blurring as a lack of spatial details. The correlation between the NR quality metrics and the well-known and most widely used objective metric, the Video Quality Model (VQM), is performed to validate the quality prediction accuracy based on the provided scores. The Pearson correlation coefficients obtained stand for promising results for different types of videos

Security and Privacy for the Internet of Things: An Overview of the Project

As the adoption of digital technologies expands, it becomes vital to build trust and confidence in the integrity of such technology. The SPIRIT project investigates the proof of concept of employing novel secure and privacy-ensuring techniques in services set-up in the Internet of Things (IoT) environment, aiming to increase the trust of users in IoTbased systems. The proposed system integrates three highly novel technology concepts developed by the consortium partners. Specifically, a technology, termed ICMetrics, for deriving encryption keys directly from the operating characteristics of digital devices; secondly, a technology based on a contentbased signature of user data in order to ensure the integrity of sent data upon arrival; a third technology, termed semantic firewall, which is able to allow or deny the transmission of data derived from an IoT device according to the information contained within the data and the information gathered about the requester

Perceptually Adaptive Lagrangian Multiplier for HEVC Guided Rate-Distortion Optimization

International audienceRecent video coding standards typically use the Rate-distortion optimization (RDO) method, which is essential to appropriately perform mode decisions during encoding process. The newest standard High Efficiency Video Coding (HEVC) introduces complex encoding structures and strong dependency between coding units. Particularly, the Lagrangian multiplier is a primary factor in RDO procedure, which directly affects the ratedistortion (R-D) performance and is defined for an entire video frame. This paper proposes a novel approach for perceptually guiding the RDO process in HEVC. The reference encoder does not consider effectively the perceptual characteristics of the input video and further, the visual sensitivity of each coding tree unit (CTU) in a frame. Inspired by the mechanisms of the human visual system, the proposed solution is a CTU-level adjustment of Lagrangian value based on a set of complementary perceptual features. The proposed scheme concerns important visual information of a CTU and its temporal dependency with adjacent blocks. Feature extraction is implemented in the frequency domain using efficient spatio-temporal analysis. In our experiments, we opted a perceptual Mean Squared Error (MSE) metric and Structural Similarity (SSIM) index. According to perceptual MSE metric, the BD-rate savings using the Bjontegaard delta measurements, were fairly convincing over the state-of-theart HEVC software HM16.12; 4.41% and 6.14% for Random Access (RA) and Low Delay (LD) encoding settings, respectively. Using SSIM, the BD-Rate achieved 6.95% and 9.86% for RA and LD settings, respectively. The proposed method further demonstrates a superior R-D performance over a compared approach adopting a similar scheme

BLIND IMAGE QUALITY ASSESSMENT IN THE COMPLEX FREQUENCY DOMAIN

International audienceIn this paper, we propose a no-reference (NR) image quality assess- ment (IQA) metric that operates in the complex frequency domain. A set of features are developed to model the natural scene statistics without depending on any specific visual distortion. The proposed approach relies on a statistical analysis of the transformed image, involving the importance of the phase and magnitude provided by the underlying complex coefficients. We further investigate the cor- relation between the different image spatial-frequency resolutions, i.e., representations under different scales and orientations in order to extract the directional features and energy distributions of an im- age. The validation of the NR metric is performed on a variety of challenging IQA databases and the obtained results show good cor- relation with subjective scores. Besides, the obtained performance is highly competitive compared to the top-performing NR IQA met- rics

Towards Perceptually Guided Rate-Distortion Optimization For HEVC

International audienceThis paper proposes a novel approach for perceptually guiding the rate-distortion optimization (RDO) process within the High Efficiency Video Coding (HEVC) standard. The reference codec does not consider effectively the perceptual characteristics of the input video and further, the particular perceptual sensitivity of each coding tree unit (CTU) inside a frame. The corresponding frame-level Lagrangian multiplier depends only on the quantization parameter. Inspired by the mechanisms of the human visual system, the proposed solution is a CTU-Ievel adjustment of the standard Lagrangian value based on a set of complementary measured features. These measures rely on the spatial and temporal analysis of the current CTU in the frequency domain. Based on perceptual quality indices and Bjontegaard delta measurements, over several resolutions of tested video sequences, the proposed method demonstrates a promising coding performance according to the rate-distortion compromise

Perceptual Video Content Analysis and Application to HEVC Quantization Refinement

International audienceIn this paper, we propose a set of perceptual features aiming to consistently describe the visual information. The measurement is performed in the complex frequency domain according to human visual system (HVS) mechanisms. The aim is to explore the performance of these features in a video coding scheme. Particularly, we consider the High Efficiency Video Coding (HEV C) standard as it introduces several efficient tools along with new coding structures. The quantization parameter (QP) is an essential factor that affects the coding performance and has a relationship the Lagrangian multiplier. Based on extracted measures, a perceptual factor is proposed to adjust the Lagrangian multiplier and subsequently, the QP is refined over the adjusted value. The achieved BD-rate savings over several resolutions of video sequences, using the Bjontegaard metric, show the promising coding efficiency of the proposed method with regard to an adequate rate-distortion (R-D) compromise. We opted for the Structural SIMilarity (SSIM) metric to carry out a perceptual R-D comparison. The R-D curves demonstrate that the obtained bitrate savings are associated to convenient quality measures, compared to HEVC anchor and a state-of-the-art QP refinement model

A Framework for Security and Privacy for the Internet of Things (SPIRIT)

International audienc