KEYWORDS: Video, Computer programming, Visualization, Detection and tracking algorithms, Video coding, Quantization, Video compression, Image processing, Video processing, Computer architecture
Nowadays, most video material is coded using a non-scalable format. When transmitting these single-layer video bitstreams, there may be a problem for connection links with limited capacity. In order to solve this problem, requantization transcoding is often used. The requantization transcoder applies coarser quantization in order
to reduce the amount of residual information in the compressed video bitstream. In this paper, we extend a requantization transcoder for H.264/AVC video bitstreams with a rate-control algorithm. A simple algorithm is proposed which limits the computational complexity. The bit allocation is based on the bit distribution in the original video bitstream. Using the bit budget and a linear model between rate and quantizer, the new quantizer is calculated. The target bit rate is attained with an average deviation lower than 6%, while the rate-distortion performance shows small improvements over transcoding without rate control.
Reduction of the bitrate of video content is necessary in order to satisfy the different constraints imposed by networks and terminals. A fast and elegant solution for the reduction of the bitrate is requantization, which has been successfully applied on MPEG-2 bitstreams. Because of the improved intra prediction in the H.264/AVC specification, existing transcoding techniques are no longer suitable. In this paper we compare requantization transcoders for H.264/AVC bitstreams. The discussion is restricted to intra 4x4 macroblocks only, but the same techniques are also applicable to intra 16x16 macroblocks. Besides the open-loop transcoder and the transcoder with mode reuse, two architectures with drift compensation are described, one in the pixel domain and the other in the transform domain. Experimental results show that these architectures approach the quality of the full decode and recode architecture for low to medium bitrates. Because of the reduced computational complexity of these architectures, in particular the transform-domain compensation architecture, they are highly suitable for real-time adaptation of video content.
KEYWORDS: Video, Quantization, Video surveillance, Video coding, Computer programming, Multimedia, Cameras, Signal to noise ratio, Raster graphics, Video compression
H.264/AVC is the newest block based video coding standard from MPEG and VCEG. It not only provides superior and efficient video coding at various bit rates, it also has a "network-friendly" representation thanks to a series of new techniques which provide error robustness. Flexible Macroblock Ordering (FMO) is one of the new error resilience tools included in H.264/AVC. Here, we present an alternative use of flexible macroblock ordering, using its idea of combining non-neighboring macroblocks together in one slice. Instead of creating a scattered pattern, which is useful when transmitting the data over an error-prone network, we divide the picture into a number of regions of interest and one remaining region of disinterest. It is assumed that people watching the video will pay much more attention to the regions of interest than to the remainder of the video. So we compress the regions of interest at a higher bit rate than the regions of disinterest, thus lowering the overall bit rate. Simulations show that the overhead introduced by using rectangular regions of interest is minimal, while the bit rate can be reduced by 30% and more in most cases. Even at those reductions the video stays pleasant to watch. Transcoders can use this information as well by reducing only the quality of the regions of disinterest instead of the quality of the entire picture if applying SNR scalability. In extreme cases the regions of disinterest can even be dropped easily, thus reducing the overall bit rate even further.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.