Abstract
The aim of this research is to find a method for providing better visual quality across the complete video sequence in H.264 video coding standard. H.264 video coding standard with its significantly improved coding efficiency finds important applications in various digital video streaming, storage and broadcast. To achieve comparable quality across the complete video sequence with the constrains on bandwidth availability and buffer fullness, it is important to allocate more bits to frames with high complexity or a scene change and fewer bits to other less complex frames. A frame layer bit allocation scheme is proposed based on the perceptual quality metric as indicator of the frame complexity. The proposed model computes the Quality Index ratio (QIr) of the predicted quality index of the current frame to the average quality index of all the previous frames in the group of pictures which is used for bit allocation to the current frame along with bits computed based on buffer availability. The standard deviation of the perceptual quality indicator MOS computed for the proposed model is significantly less which means the quality of the video sequence is identical throughout the full video sequence. Thus the experiment results shows that the proposed model effectively handles the scene changes and scenes with high motion for better visual quality.
Highlights
The success of digital video application commercially resets with its ability to deliver constant quality video which is better for the given bandwidth and performance constrains
A rate control model which decides the quantization step size and monitors the buffer overflow and underflow conditions is another important module in the video encoding
Rate control model is a two-step process, in the first step arrive at a frame layer bit allocation and in the second step calculate the quantization step size which meets the allocated buffer constrains
Summary
The success of digital video application commercially resets with its ability to deliver constant quality video which is better for the given bandwidth and performance constrains. A rate control model which decides the quantization step size and monitors the buffer overflow and underflow conditions is another important module in the video encoding. Rate control model is a two-step process, in the first step arrive at a frame layer bit allocation and in the second step calculate the quantization step size which meets the allocated buffer constrains. Even though this encoding module is not explained in the standard and it is left open for application specific implementation, normally it is associated with a buffer model specified in the video coding standard. A leaky bucket model is normally employed in encoder to characterize the Hypothetical Reference Decoder (HRD) and its input buffer called Coded Picture Buffer (CPB) to avoid the buffer overflow and underflow in the decoder
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