Abstract
In recent years, the wireless mobile markets are witnessing an unprecedented growth. High-quality video service will be greatly needed as one of the hottest wireless multimedia services in the future generation wireless networks. In this paper, a novel content-based distortion control scheme is proposed to provide higher quality of the wireless video services. Our scheme adopts rate-distortion optimization techniques in state-of-the-art video coding standard H.264/AVC. In order to improve the subjective video quality in the process of encode, we create three visual distortion sensitivity models to minimize the perceptual distortion. We arrange more bits to visual distortion sensitive macroblocks during rate-distortion optimization process. The perceptual distortion in these regions is thus efficiently controlled with a relatively higher rate. Meanwhile, rate balance is achieved by allotting fewer bits to macroblocks that are perceptually less sensitive to distortion. Experiments results show that the subjective qualities of encoded video are improved without compromising PSNR.
Highlights
In recent years, the wireless mobile markets are witnessing an unprecedented growth
Our work aims at offering high quality of service (QoS) in future generation wireless networks (FGWNs) by improving subjective coding quality of the video coder without varying bitrate
Because of the high throughput ability of FGWN and high fidelity video services required by prospective customers, we set comparatively high bitrates in our experiments, which are between 120 kbps and 550 kbps
Summary
The wireless mobile markets are witnessing an unprecedented growth. As the enormous increase of mobile device users, more wireless information services, and mobile commerce applications are demanded. Apart from these, in very recent literatures, some methods are suggested to adjust Lagrange multipliers by considering perceptual characters of the video content [11, 12] Both of the RDO schemes in [11, 12] can effectively distinguish texture regions, edged regions, and flat regions of the encoded frame, and arrange different λ to these regions according to their contents. We incorporate three important visual features into video coding and further establish three visual distortion sensitivity models These models are used for minimizing the perceptual distortion and helping to adjust λ adaptively in accordance with the video contents in the RDO process.
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