Xiaoan Lu

A new source model and accurate rate control algorithm with QP and rounding offset adaptation

Rate control plays an important role in regulating the encoding bit rate to meet the bandwidth and storage requirement. Most existing works regulate the bit rate by adjusting the quantization step size. We propose to incorporate a new dimension: the quantization rounding offset into a rate control algorithm. Based on our previous work of multi-pass fine rate control, in this work, we present a unified one-pass rate control algorithm that jointly adjusts the quantization step size and the rounding offset for high bit rate accuracy. Unlike the quantization step size that has a limited number of choices, the rounding offset is a continuously adjustable variable that allows the rate control algorithm to reach any precision in principle. Our extensive experimental results show that the proposed algorithm greatly improves the rate control accuracy at almost no extra computational complexity.

A novel fine rate control algorithm with adaptive rounding offset

The rate control algorithm is of essential importance to a video encoder. It enables the encoded bitstream to meet the bandwidth and storage requirement while maintaining good video quality. Most existing works adjust the quantization step size to achieve the required bit rate accuracy. This paper introduces a new dimension: the quantization rounding offset into a frame-level fine rate control algorithm. Specifically, we propose a novel fine rate control algorithm based on a linear model between the bit rate and the rounding offset. Unlike the quantization step size that has a limited number of choices, the quantization rounding offset is a continuously adjustable variable which allows the rate control algorithm to reach any precision in principle. Extensive experiment results show that the proposed algorithm greatly improves the bit rate accuracy and provides better visual quality by fine tuning of the rounding offset in addition to the quantization step size.

A Fine Rate Control Algorithm With Adaptive Rounding Offsets (ARO)

Rate control plays an important role in regulating the bit rate to meet the bandwidth and storage requirement. Most existing video encoders regulate the bit rate by adjusting the quantization step size. We propose to incorporate a new dimension: the quantization rounding offset into rate control. In this paper, we present a rate control algorithm with adaptive rounding offsets (ARO) that jointly adjusts the quantization step size and the rounding offset for high bit rate accuracy. Different from the quantization step size that has a limited number of choices, the rounding offset is a continuously adjustable variable that allows the rate control algorithm to reach any precision in principle. Our extensive experimental results show that the proposed ARO algorithm significantly improves the rate control accuracy at almost no extra computational complexity. Compared with the rho-domain rate control, the ARO algorithm reduces the rate control errors from about 2% to 0.5% for INTRA frames, and 5% to 1.5% for INTER frames. Our experiments also demonstrate that ARO provides the extra benefit of smoother visual quality.

A New Spatial Activity Metric for Film Contents

The masking property of human vision systems has been successfully applied in various image/video applications. To invoke the spatial masking effect, it is important to design a metric that effectively identifies the spatial activity of a region. This metric indicates which areas are more textured and more artifacts can be masked. We review three widely used metrics and evaluate their performance in context of film content. We observe that these metrics have strong dependencies on the brightness. More specifically, for smooth areas with film grain, these metrics usually assign greater degrees of texture to the bright regions and lower degrees to dark ones. This causes problems in the bright areas that are mistakenly identified as more textured than the dark areas. Utilizing the property of film grain, we explain the origin of this dependency and propose a new spatial activity metric that removes the dependency on the brightness. In our simulation, we use this new metric in the rate control algorithm of a MPEG-2 video encoder. The result shows more homogeneous film grain in the reconstructed pictures and improved visual quality.