极化码在压缩图像传输系统中的性能改进方法
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摘要
为了解决图像经压缩去冗余编码后易受干扰的问题,提出一种Polar码在嵌入式零树小波(EZW)压缩图像传输系统中的性能改进方法。在总码率一定的情况下,通过简化组合最优算法,完成对原始压缩码流的分段以及码率分配。根据Polar码存在的不等错误属性和同一段内码流重要性不同,完成不等错误保护。通过仿真,提出的改进方法有效改善了标准Polar码在低信噪比和低密度奇偶校验码(LDPC)码在高信噪比条件下性能表现差的问题,其中,当信噪比为1 d B时,相比于传统Polar码,改进方法重构图像的峰值信噪比(PSNR)值提高了5 d B,相对于LDPC码,对应的PSNR值提高了4 d B。经EZW编码后的码流以重要性进行排序,并不依赖图像信源,因此该方法具有很好的通用性。
An approach which improves the Polar codes performance in image compression system by embedded zero tree wavelet encoding is proposed to solve the problem that image is susceptible to interference after compression and redundant coding. When the total bit rate is constant,the segmentation and rate allocation of original compressed bit stream are completed by simplifying the optimal combination algorithm. The unequal error protection is completed based on different error attributes of polar codes and different significance of bit stream within the same segmentation. Through simulation,the proposed method improves the low performance of standard Polar code in low signal to noise ratio( SNR)and the low-density parity check( LDPC) code under high SNR. When the SNR is 1 Db,the peak signal-to-noise ratio( PSNR) of the reconstructed image is improved by 5 d B compared to the conventional Polar code,and the corresponding PSNR value is increased by 4 d B relative to the LDPC code. The EZW encoded stream is sorted by significance with no reliance on image source,which means this method has good generality.
An approach which improves the Polar codes performance in image compression system by embedded zero tree wavelet encoding is proposed to solve the problem that image is susceptible to interference after compression and redundant coding. When the total bit rate is constant,the segmentation and rate allocation of original compressed bit stream are completed by simplifying the optimal combination algorithm. The unequal error protection is completed based on different error attributes of polar codes and different significance of bit stream within the same segmentation. Through simulation,the proposed method improves the low performance of standard Polar code in low signal to noise ratio( SNR)and the low-density parity check( LDPC) code under high SNR. When the SNR is 1 Db,the peak signal-to-noise ratio( PSNR) of the reconstructed image is improved by 5 d B compared to the conventional Polar code,and the corresponding PSNR value is increased by 4 d B relative to the LDPC code. The EZW encoded stream is sorted by significance with no reliance on image source,which means this method has good generality.
引文
[1]汪亚芬,汪汉新.基于压缩感知和非对称Turbo码的联合信源信道编码[J].计算机应用与软件,2015,32(8):110-113.
[2]Moses M B,Pradeep N S.Performance improvement of MaxLog-MAP Turbo decoding algorithm using optimized scaling factor for image transmission and retrieval[C]//International Conference on Green Computing and Internet of Things.IEEE,2015:1161-1167.
[3]Baviskar J,Mulla A,Vaswani P,et al.Adaptive matrix design for LDPC based image processing system[C]//International Conference on Advances in Computing,Communications and Informatics.IEEE,2014:2374-2379.
[4]Qazi S A,Shoaib M,Javaid U,et al.A comparative analysis of LDPC decoders for image transmission over AWGN channel[C]//International Conference on Frontiers of Information Technology.ACM,2009:4.
[5]Arikan E.Channel Polarization:A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels[J].IEEE Transactions on Information Theory,2009,55(7):3051-3073.
[6]Telatar E.Polar coding:A brief tour[C]//International Conference on Signal Processing and Communications.IEEE Xplore,2010:1-2.
[7]王军选,张燕燕.极化码及性质[J].现代电子技术,2012,35(1):65-67.
[8]施鹏,郑芝芳,巩龙延,等.Polar码在图像传输中的性能研究[J].南京邮电大学学报(自然科学版),2014,34(2):65-71.
[9]Payommai T,Chamnongthai K.Performance of polar code for image transmission[C]//International Symposium on Intelligent Signal Processing and Communications Systems.IEEE,2013:450-453.
[10]Du W,Zhang S,Ding F.Exploiting the UEP property of polar codes to reduce image distortions induced by transmission errors[C]//Ieee/cic International Conference on Communications in China.IEEE,2015:1-5.
[11]朱柳泉,孙娜,肖东亮.一种基于Polar码的可抗差错图像传输方法[J].无线电工程,2016(1):30-33.
[12]Ashwin D M R,Ahamad M G,Ravichandran D.Medical image compression using Embedded Zerotree Wavelet(EZW)coder[C]//System Modeling&Advancement in Research Trends.IEEE,2017.
[13]Kong B Y,Yoo H,Park I C.Efficient Sorting Architecture for Successive-Cancellation-List Decoding of Polar Codes[J].IEEE Transactions on Circuits&Systems II Express Briefs,2016,63(7):673-677.
[14]Niu K,Chen K.CRC-Aided Decoding of Polar Codes[J].IEEE Communications Letters,2012,16(10):1668-1671.
[15]徐真珍,曾辉,胡凯.基于提升小波的两阶段多描述图像编码[J].计算机应用与软件,2016,33(4):192-195.
[16]Mackay D J C.Good Error-Correcting Codes based on Very Sparse Matrices[J].IEEE Transactions on Information Theory,1999,45(2):399-431.
[2]Moses M B,Pradeep N S.Performance improvement of MaxLog-MAP Turbo decoding algorithm using optimized scaling factor for image transmission and retrieval[C]//International Conference on Green Computing and Internet of Things.IEEE,2015:1161-1167.
[3]Baviskar J,Mulla A,Vaswani P,et al.Adaptive matrix design for LDPC based image processing system[C]//International Conference on Advances in Computing,Communications and Informatics.IEEE,2014:2374-2379.
[4]Qazi S A,Shoaib M,Javaid U,et al.A comparative analysis of LDPC decoders for image transmission over AWGN channel[C]//International Conference on Frontiers of Information Technology.ACM,2009:4.
[5]Arikan E.Channel Polarization:A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels[J].IEEE Transactions on Information Theory,2009,55(7):3051-3073.
[6]Telatar E.Polar coding:A brief tour[C]//International Conference on Signal Processing and Communications.IEEE Xplore,2010:1-2.
[7]王军选,张燕燕.极化码及性质[J].现代电子技术,2012,35(1):65-67.
[8]施鹏,郑芝芳,巩龙延,等.Polar码在图像传输中的性能研究[J].南京邮电大学学报(自然科学版),2014,34(2):65-71.
[9]Payommai T,Chamnongthai K.Performance of polar code for image transmission[C]//International Symposium on Intelligent Signal Processing and Communications Systems.IEEE,2013:450-453.
[10]Du W,Zhang S,Ding F.Exploiting the UEP property of polar codes to reduce image distortions induced by transmission errors[C]//Ieee/cic International Conference on Communications in China.IEEE,2015:1-5.
[11]朱柳泉,孙娜,肖东亮.一种基于Polar码的可抗差错图像传输方法[J].无线电工程,2016(1):30-33.
[12]Ashwin D M R,Ahamad M G,Ravichandran D.Medical image compression using Embedded Zerotree Wavelet(EZW)coder[C]//System Modeling&Advancement in Research Trends.IEEE,2017.
[13]Kong B Y,Yoo H,Park I C.Efficient Sorting Architecture for Successive-Cancellation-List Decoding of Polar Codes[J].IEEE Transactions on Circuits&Systems II Express Briefs,2016,63(7):673-677.
[14]Niu K,Chen K.CRC-Aided Decoding of Polar Codes[J].IEEE Communications Letters,2012,16(10):1668-1671.
[15]徐真珍,曾辉,胡凯.基于提升小波的两阶段多描述图像编码[J].计算机应用与软件,2016,33(4):192-195.
[16]Mackay D J C.Good Error-Correcting Codes based on Very Sparse Matrices[J].IEEE Transactions on Information Theory,1999,45(2):399-431.
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