Proc. SPIE. 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications
KEYWORDS: Clocks, Image processing, Video, Field programmable gate arrays, Computer programming, Very large scale integration, Video processing, Real time video processing, Standards development, Video coding
H.264 is the newest video coding standard and is currently one of the hot subjects of video processing technologies.
Coding quality and compression ratio have been greatly improved in the new standard compared with the previous
standards. The context-based adaptive technology is introduced into the new standard, which can be said to be a
technology renovation of the video coding. The main entropy coding technologies of H.264 include VLC (Variable-
Length Coding) and CABAC (Context-based Adaptive Binary Arithmetic Coding). CAVLC is VLC and adopts the
context-based adaptive technology, therefore the coding efficiency is greatly improved. Currently, the design of the
CAVLC encoder is mainly in software method, but with the development of real-time video processing technology, it is
difficult for software to meet the demands. As a result, the hardware method in designing of CAVLC coder becomes a
good choice. In the paper a CAVLC entropy encoder architecture based VLSI is proposed and implemented on an Altera
FPGA device. As the results of simulation and synthesis, it can process 4×4 or 2×2 blocks per 16 clock periods with
pipelined architecture and can achieve the real-time processing requirement of 30 frames per second for a 720×480 video
at 100 MHz operation frequency.
The intra prediction algorithm is one of the key algorithms provided by H.264, which contributes to high compression
ratio. Unfortunately it considerably increases the complexity of the encoder. A fast intra prediction algorithm is proposed
based on the existing algorithms, in which last prediction mode is the prior consideration for current predict mode. It has
been simulated with Matlab. Experimental results show, comparing to the search algorithm presented by JM code, the
proposed algorithm can reduce approximately 41 and 59 percent of the cost of mode search and achieve about 93 and 63
percent of precision on the average for 4×4 and 16×16 prediction mode, respectively.