Sorry, you need to enable JavaScript to visit this website.

In order to achieve highly compact representation for videos, we propose an adaptive quantization based perceptual video coding (PVC) scheme in this paper. Because human only perceive the limited discrete-scale quality levels, the perceptual quantization is transformed into the problem of how to determine the maximum quantization parameter (Qp) under the same perceptual quality level. So, the relationship between perceptual quality level and quantization parameter is analyzed with the statistical way in this paper.

Adaptive HTTP streaming is the preferred method to deliver multimedia content in the internet. It provides multiple representations of the same content in different qualities (i.e. bit-rates and resolutions) and allows the client to request segments from the available representations in a dynamic, adaptive way depending on its context. The growing number of representations in adaptive HTTP streaming makes encoding of one video segment at different representations a challenging task in terms of encoding time-complexity.

Modern video codec uses arithmetic coding for entropy coding. The arithmetic coding asymptotically achieves the entropy bound provided the true probability distribution. Hence the compression efficiency heavily relies on the ability to capture the time-variant probability model in video signals. Variants of first-order linear probability model update schemes have been used in recent generation video codecs. Built on top of those, a multimodal estimation scheme that forms a higher order probability model update has been proposed in this work.

High-Efficiency Video Coding (HEVC) is the latest video coding standard which is developed by the Joint Collaborative Team on Video Coding (JCT-VC). To guarantee successful transmission and to make the best use of available network resources, an effective rate control mechanism plays a critical role in video coding standards. The coding performance can be maximised through the appropriate allocation of bits under the constraints of a total bit rate budget and the buffer size.

This paper proposes a rate control algorithm based on group of pictures (GOP) level quality dependency for high efficiency video coding (HEVC) low delay hierarchical coding structure. Firstly, this paper builds a GOP level quality dependency model. Secondly, a GOP level quality dependency model based GOP level rate-distortion optimization is introduced to make bit allocation more reasonable.

Inserting a logo into HEVC video streams is highly demanded in video applications. In this paper, we present an efficient logo insertion method for video coding in HEVC. To reduce the impact of inserted logo, the proposed method mitigates the encoding dependence on logo by partitioning the video frame into separated regions. For lossless coding region, we reduce the bit rate overhead of lossless coding according to an error propagation model. For information reusing region, we partly re-encode the quality-loss area to maintain the encoding quality.