Video quality

About: Video quality is a research topic. Over the lifetime, 13143 publications have been published within this topic receiving 178307 citations.

A video texture database for perceptual compression and quality assessment

Abstract: This paper presents a new publicly available video texture database (BVI Texture) that contains test sequences and subjective opinion scores. The database exhibits a wide range of static and dynamic textures together with some mixed content. Each sequence is indexed using various video feature descriptors that characterize its spatial activity, temporal activity, static texture content and dynamic texture content. Moreover, rate/distortion results for the new dataset are presented after compression using HEVC, alongside subjective quality evaluation data. The BVI texture database will provide utility in testing quality assessment metrics and emerging video compression methods, particularly those based on texture analysis and synthesis.

A General Method for Detecting All-Zero Blocks Prior to DCT and Quantization

Abstract: This paper presents an innovative algorithm for detecting all-zero discrete cosine transform (DCT) coefficient blocks prior to DCT and quantization for all block-based video coding standards. A mathematic model is established based on analyzing DCT coefficient distribution and applying Paseval energy conservation theorem. The algorithm is applied to H.264 video coding and experimental results show up to 32% higher detection ratio without degrading video quality, compared with results of the existing methods. Furthermore, up to 47% higher detection ratio is achieved by changing the threshold based on DCT coefficient distribution. For motion estimation, much less search points needed by using the proposed method as early termination criterion than that by using the existing methods

QRP08-1: Opinion Model for Estimating Video Quality of Videophone Services

Abstract: We propose a computational opinion model for estimating video quality of videophone services. Opinion models for speech such as the E-model have been established and widely used; however, little attention has been given to opinion models for video quality estimation. Our proposed opinion model is useful as a network-planning tool for assessing several video parameters that affect the quality of videophone services. First, we established a function for estimating video quality affected by coding degradation, which expresses the quality of a video affected by coding bit rate and frame rate. Second, we established a packet loss degradation index that estimates the degree of video quality degradation due to packet loss. Finally, we integrated these two functions into the opinion model for estimating video quality. We applied this model for video quality estimation of a videophone service with various video formats and displayed video sizes. The results indicated that the estimation errors of our model were less than the mean of the 99% confidence intervals for the subjective scores. Therefore, our model could be applied to effective design, implementation, and management of videophone applications and communication networks.

A Temporal Error Concealment Method for H.264/AVC Using Motion Vector Recovery

Abstract: Recently H.264/AVC is rapidly deployed in the mobile multimedia market, such as terrestrial and satellite DMB (digital multimedia broadcasting), and Internet multimedia streaming systems. To provide the better quality under the unreliable communication environments, we propose a motion vector (MV) recovery method for the temporal error concealment. The H.264/AVC adopts the various block sizes for the motion estimation and compensation, ranging from 16times16 to 4times4 block sizes. To increase the accuracy in the temporal error concealment, the 4times4 block size is used as the MV recovery unit. Flexible MB ordering (FMO) option, by which the neighboring MBs can be transmitted in the different packets, is used. The MVs of the lost MBs are recovered based on the MV tendency which is derived from the neighboring MVs. The simulation results show that the proposed method improves video quality up to 2.95dB and 2.45dB, compared with the H.264/AVC test model and Lagrange interpolation method, respectively.

3D Data Representation, Conveyance, and Use

Abstract: 3D video can be transmitted in a legacy 2D video format by conveying 3 rd dimension parameters within a steganographic channel of the perceptual video signal, e.g., DCT coefficients, video samples (luminance, chrominance values), etc. The 3 rd dimension parameters can be coded as depth values, disparity, displacement, difference, or parallax values, including depth that is converted into X-Y shifts for adjustment to motion vectors in coded video sequence. To limit the amount of information for the steganographic channel, the 3 rd dimension information can be quantized relative to the depth from viewer and other prioritization parameters that limit the need for 3 rd dimension information to only aspects of the scene that are deemed important to create a desired 3D effect.