为提高Exp-Golomb码的编解码效率,提出了一种基于快速"首位1检测"的Exp-Golomb编解码器硬件实现方法,降低了计算量并节省了硬件资源。该Exp-Golomb编解码器已通过RTL(Register Transfer Level)级仿真和综合,并在FPGA(Field Pr...为提高Exp-Golomb码的编解码效率,提出了一种基于快速"首位1检测"的Exp-Golomb编解码器硬件实现方法,降低了计算量并节省了硬件资源。该Exp-Golomb编解码器已通过RTL(Register Transfer Level)级仿真和综合,并在FPGA(Field Programmable Gate Array)开发平台进行了验证,在133 MHz时钟频率下编解码器的综合门数分别为765门和632门。该编解码器能满足Baseline档次(30帧/s),分辨率为352×288视频序列的实时编解码对质量和速度的要求。展开更多
Most of multimedia schemes employ variable-length codes （VLCs） like Huffman code as core components in obtaining high compression rates. However VLC methods are very sensitive to channel noise. The goal of this pape...Most of multimedia schemes employ variable-length codes （VLCs） like Huffman code as core components in obtaining high compression rates. However VLC methods are very sensitive to channel noise. The goal of this paper is to salvage as many data from the damaged packets as possible for higher audiovisual quality. This paper proposes an integrated joint source-channel decoder （I-JSCD） at a symbol-level using three-dimensional （3-D） trellis representation for first-order Markov sources encoded with VLC source code and convolutional channel code. This method combines source code and channel code state-spaces and bit-lengths to construct a two-dimensional （2-D） state-space, and then develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol. Experiment results demonstrate that our method results in significant improvement in decoding performance, it can salvage at least half of （50%） data in any channel error rate, and can provide additional error resilience to VLC stream like image, audio, video stream over high error rate links.展开更多
为了进一步降低高性能视频编码(HEVC)的输出码率,针对基于上下文的自适应算术编码(CABAC),提出了一种改进算法。利用大尺寸变换单元(TU)和变换跳过模式系数块大值系数较多的特点,首先在32×32变换单元中,根据已编码4×4系数组(...为了进一步降低高性能视频编码(HEVC)的输出码率,针对基于上下文的自适应算术编码(CABAC),提出了一种改进算法。利用大尺寸变换单元(TU)和变换跳过模式系数块大值系数较多的特点,首先在32×32变换单元中,根据已编码4×4系数组(CG)系数值的分布特性,自适应决定下一个CG的哥伦布-莱斯(Golomb-Rice)初始参数值;其次,在变换跳过模式系数块中设置初始Golomb-Rice参数为1,再利用相邻系数的相关性,根据已编码系数绝对值大小自适应决定下一系数的编码参数值。实验结果表明,与HEVC标准算法HM16.0相比,所提算法能达到0.09%~2.75%的比特率下降,平均有效率90%以上,且峰值信噪比(PSNR)无损失,编码时间平均只增加了0.08%。与代表文献相比,所提算法平均节省0.49%比特率,PSNR平均提高0.01 d B。展开更多
测试数据的规模和容量直接影响了片上系统的测试成本,故提出了一种测试数据编码的压缩算法———M in Comp.该方法采用不等间距的编码方式,根据测试数据中游程长度的统计分布情况来调整各组数据的大小,从而提高测试数据的压缩率,降低了...测试数据的规模和容量直接影响了片上系统的测试成本,故提出了一种测试数据编码的压缩算法———M in Comp.该方法采用不等间距的编码方式,根据测试数据中游程长度的统计分布情况来调整各组数据的大小,从而提高测试数据的压缩率,降低了测试成本.为了使编码算法对应的解码电路的硬件开销最小化,该算法还引入了前后缀标识位的概念,这样可减小解码电路的规模和复杂度.对ISCAS89benchm ark电路的实验结果表明,采用M in Comp编码方式的压缩效率要比Golomb等编码方法好,而且实现方式简单.展开更多
基金Supported by the Foundation of Ministry of Education of China (211CERS10)
文摘Most of multimedia schemes employ variable-length codes （VLCs） like Huffman code as core components in obtaining high compression rates. However VLC methods are very sensitive to channel noise. The goal of this paper is to salvage as many data from the damaged packets as possible for higher audiovisual quality. This paper proposes an integrated joint source-channel decoder （I-JSCD） at a symbol-level using three-dimensional （3-D） trellis representation for first-order Markov sources encoded with VLC source code and convolutional channel code. This method combines source code and channel code state-spaces and bit-lengths to construct a two-dimensional （2-D） state-space, and then develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol. Experiment results demonstrate that our method results in significant improvement in decoding performance, it can salvage at least half of （50%） data in any channel error rate, and can provide additional error resilience to VLC stream like image, audio, video stream over high error rate links.
文摘为了进一步降低高性能视频编码(HEVC)的输出码率,针对基于上下文的自适应算术编码(CABAC),提出了一种改进算法。利用大尺寸变换单元(TU)和变换跳过模式系数块大值系数较多的特点,首先在32×32变换单元中,根据已编码4×4系数组(CG)系数值的分布特性,自适应决定下一个CG的哥伦布-莱斯(Golomb-Rice)初始参数值;其次,在变换跳过模式系数块中设置初始Golomb-Rice参数为1,再利用相邻系数的相关性,根据已编码系数绝对值大小自适应决定下一系数的编码参数值。实验结果表明,与HEVC标准算法HM16.0相比,所提算法能达到0.09%~2.75%的比特率下降,平均有效率90%以上,且峰值信噪比(PSNR)无损失,编码时间平均只增加了0.08%。与代表文献相比,所提算法平均节省0.49%比特率,PSNR平均提高0.01 d B。
文摘测试数据的规模和容量直接影响了片上系统的测试成本,故提出了一种测试数据编码的压缩算法———M in Comp.该方法采用不等间距的编码方式,根据测试数据中游程长度的统计分布情况来调整各组数据的大小,从而提高测试数据的压缩率,降低了测试成本.为了使编码算法对应的解码电路的硬件开销最小化,该算法还引入了前后缀标识位的概念,这样可减小解码电路的规模和复杂度.对ISCAS89benchm ark电路的实验结果表明,采用M in Comp编码方式的压缩效率要比Golomb等编码方法好,而且实现方式简单.
