Visual Quality Of Compressed Video Research Articles

Latitude-Based Flexible Complexity Allocation for 360-Degree Video Coding

The emerging 360-degree video has a good practical prospect in video broadcasting due to its more immersive experience than traditional videos. To maintain a high fidelity with panoramic vision, 360-degree video adopts a significantly increased resolution than planar videos, which also inevitably leads to higher encoding complexity. In this paper, we propose a flexible complexity optimization method for 360-degree video coding, in which the encoder is capable of adapting to different complexity constraints in diversified broadcasting scenarios. In particular, the proposed method is realized with a latitude-based computation complexity allocation. Firstly, it investigates the Coding Unit (CU) partition variation along the latitude (i.e., vertical axis) and divides each video frame into Largest CU (LCU)-based latitude regions. Then, it formulates the complexity allocation problem from the global complexity target to all latitude regions, by considering the intraframe dependencies and Rate-Distortion (RD) models. Finally, it calculates the solution to this complexity allocation problem and further employs it in 360-degree video coding. Comprehensive experiments on the standard dataset reveal the superiority of our method, which achieves a flexible computational time reduction from 14.53% to 68.36% whilst maintaining a high visual quality of compressed videos.

Novel PID-Fuzzy Video Rate Controller for High-Delay Applications of the HEVC Standard

The new High Efficiency Video Coding (HEVC) standard is targeted for high-resolution video contents that are suitable for many high-delay video communications applications, such as video streaming. A few-rate control algorithms (RCAs) have been proposed for the HEVC in the literature. Almost all state-of-the-art RCAs proposed for the HEVC are optimized for constant bit rate low-delay applications. In order to reach a higher visual quality in high-delay applications, such as video streaming, a proportional integral derivative (PID)-fuzzy RCA with the buffering constraint is proposed for the HEVC in this paper. The proposed RCA is designed to minimize fluctuations of quantization parameter (QP) while the buffering constraints are fully obeyed. Unlike conventional fuzzy-PID algorithms that use a PID controller for control and a fuzzy system for tuning the PID parameters, the proposed algorithm uses a fuzzy controller with proportional, integral, and derivative inputs. A base QP is calculated for each group of picture (GOP) by the PID-fuzzy controller and determined QP offsets are added to the base QP to obtain the QP of frames at different temporal layers in the GOP. Experimental results indicate that high rate-distortion performance, fulfilled buffering constraint, and the high visual quality of compressed video are gained simultaneously by the proposed algorithm with low computational complexity.

Robust FMO algorithm and adaptive redundant slice allocation for wireless video transmission

Visual quality of compressed video may suffer great degradation when transmitted over lossy wireless networks. Flexible macro-block ordering (FMO) is a new error resilient tool adopted by H.264/AVC. It has a good performance of error resilience by changing the coding order of macro-blocks in the frame. redundant slice (RS) is another tool which adds redundant copy of slices into the stream to take precautions against packet loss. However, we shouldn't only care about peak signal to noise ratio (PSNR) of the video; the robustness of video streams to burst packet loss of wireless channel is also worth considering. In applications, such as real-time video transmission services, degradation of video quality may be tolerable, but collapse of decoder due to burst packet loss will greatly lower user's quality of experience. This paper proposes a robust FMO (RFMO) algorithm which takes gradient feature of frames into consideration to enhance robustness of video streams, and the adaptive RS allocation (ARSA) helps to increase the PSNR with only a little increase in bit rate. Experiment results show that the RFMO algorithm can significantly reduce the collapse times of decoder with invisible decrease in visual quality, and the ARSA can still guarantee a high PSNR in the case of high packet loss rate.

SSIM-based Error Resilient Video Coding Over Packet-Switched Networks

The visual quality is a critical factor in prediction video coding over packet-switched networks. However, the traditional MSE-based error resilient video coding cannot correlate well with the perceptual characteristics of the human visual system (HVS). This paper proposes a structural similarity (SSIM) based error resilient video coding scheme to improve the visual quality of compressed videos over packet-switched networks. In the proposed scheme, a SSIM-based end-to-end distortion model is developed to estimate the perceptual distortion due to quantization, error concealment, and error propagation. Based on this model, an adaptive mode selection strategy is presented to enhance the communication robustness of compressed videos. Experiments show that the proposed scheme significantly improves the visual quality for H.264/AVC video coding over packet-switched networks.

Perceptually Scalable Extension of H.264

We propose a novel visual scalable video coding (VSVC) framework, named VSVC H.264/AVC. In this approach, the non-uniform sampling characteristic of the human eye is used to modify scalable video coding (SVC) H.264/AVC. We exploit the visibility of video content and the scalability of the video codec to achieve optimal subjective visual quality given limited system resources. To achieve the largest coding gain with controlled perceptual quality degradation, a perceptual weighting scheme is deployed wherein the compressed video is weighted as a function of visual saliency and of the non-uniform distribution of retinal photoreceptors. We develop a resource allocation algorithm emphasizing both efficiency and fairness by controlling the size of the salient region in each quality layer. Efficiency is emphasized on the low quality layer of the SVC. The bits saved by eliminating perceptual redundancy in regions of low interest are allocated to lower block-level distortions in salient regions. Fairness is enforced on the higher quality layers by enlarging the size of the salient regions. The simulation results show that the proposed VSVC framework significantly improves the subjective visual quality of compressed videos.