Fast Rate Distortion Optimized Quantization for H.264/AVC
Jiangtao Wen, Mou Xiao, Jianwen Chen, Pin Tao, Chao Wang
Abstract
Jiangtao Wen, Mou Xiao, Jianwen Chen, Pin Tao, Chao Wang
Abstract
In this paper, a fast RDO (rate-distortion optimization) quantization algorithm for H.264/AVC is proposed. In this algorithm, the searching space of level adjustments is reduced by filtering the input quantized coefficients in a hierarchical way. The well quantized coefficients is first filtered out, and then the RD tradeoff of each level adjustment to each of the rest coefficients is examined to select some good candidates with their associated level adjustments. Finally these good candidates are combined to find the best combination of level adjustments which gives the minimal rate-distortion cost. Furthermore, a fast rate estimation technique is adopted to save the rate-distortion estimation time. Experimental results show that about 44% quantization time on average can be saved at the cost of negligible PSNR loss compared with RDO quantization algorithm implemented in JM.
OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this paper, a fast RDO (rate-distortion optimization) quantization algorithm for H.264/AVC is proposed. In this algorithm, the searching space of level adjustments is reduced by filtering the input quantized coefficients in a hierarchical way. The well quantized coefficients is first filtered out, and then the RD tradeoff of each level adjustment to each of the rest coefficients is examined to select some good candidates with their associated level adjustments. Finally these good candidates are combined to find the best combination of level adjustments which gives the minimal rate-distortion cost. Furthermore, a fast rate estimation technique is adopted to save the rate-distortion estimation time. Experimental results show that about 44% quantization time on average can be saved at the cost of negligible PSNR loss compared with RDO quantization algorithm implemented in JM.
Key concepts: Quantization (signal processing), Algorithm, Rate–distortion optimization, Rate distortion, Computer science, Distortion (music), Mathematical optimization, Rate–distortion theory