Hardware implementation of lossless image compression

WANG Jian-jun; LIU Bo

doi:10.3788/OPE.20111904.0922

您当前的位置：

首页 >

文章列表页 >

Hardware implementation of lossless image compression

Article | 更新时间：2020-08-12

- Hardware implementation of lossless image compression
- Optics and Precision Engineering Vol. 19, Issue 4, Pages: 922-928(2011)
- 作者机构：
  
  1. 中国人民武装警察部队工程学院,陕西西安,710086
  2. 中国科学院空间科学与应用研究中心, 北京 1001909
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20111904.0922
  CLC： TP391.4
- Received：11 June 2010，
  
  Revised：03 September 2010，
  
  Published Online：26 April 2011，
  
  Published：26 April 2011
- 稿件说明：
移动端阅览
王建军, 刘波. 适于硬件实现的无损图像压缩[J]. 光学精密工程, 2011,19(4): 922-928

WANG Jian-jun, LIU Bo. Hardware implementation of lossless image compression[J]. Editorial Office of Optics and Precision Engineering, 2011,19(4): 922-928
王建军, 刘波. 适于硬件实现的无损图像压缩[J]. 光学精密工程, 2011,19(4): 922-928 DOI： 10.3788/OPE.20111904.0922.

WANG Jian-jun, LIU Bo. Hardware implementation of lossless image compression[J]. Editorial Office of Optics and Precision Engineering, 2011,19(4): 922-928 DOI： 10.3788/OPE.20111904.0922.

摘要

针对常见嵌入式小波编码算法硬件实现困难、成本较高等问题

提出了一种适用于硬件实现的无损图像压缩算法。该算法根据子带属性的不同将小波系数分为1个低频子块和3个高频子块

然后使用不同的方法分别进行量化编码。对于低频子块

首先使用脉冲差分编码调制(DPCM)方法压缩其数据动态

然后使用改进的比特位平面编码算法编码输出对应码流;对于各高频子块

则使用提出的改进集合树分裂(SPIHT)算法分别进行量化编码。在改进的SPIHT算法中

通过加入A类集合的分类优化了码流输出;通过消除链表

降低了内存需求并避免了内存的动态管理;通过使用集合极值矩阵

避免了扫描过程中的重复判断

提高了编码效率。实验结果表明

与传统SPIHT算法相比

本文算法可使各国际标准测试图像的编码比特率均降低0.14 bit/pixel以上

而编码速度提高3倍以上。该算法具有实时性高、内存需求低、适于硬件实现的特点。

Abstract

A hardware implementation method for lossless image compression is proposed to overcome the difficulties of embedded wavelet coding methods in hardware implementation and high costs. Firstly

the algorithm divides wavelet coefficients into a low frequency block and three high frequency blocks according to sub-band properties

and then uses different methods to code respectively. In the low frequency block coding method

the Difference Pulse coding Modulation(DPCM) is firstly used to reduce coefficients' dynamic range. Then

a modified bit plane coding method is used to output the bit stream. In the high frequency block coding method

the proposed modified Set Partitioning in Hierarchical trees(MSPIHT) algorithm is used to code three high frequency blocks respectively with their thresholds.The MSPIHT optimizes the outputted bit stream by using a type of A set judge

reduces memory requirement and avoids memory dynamic management by eliminating the lists of SPIHT algorithm.Moreover

the MSPIHT avoids repeated calculation in scanning process and enhances the coding efficiency by adopting MMVS. Experiment results show that the bit-rates of all international standard testing images have reduced more than 1.4 bit/pixel and the coding speed has increased more than three times as compared with that SPHIT. It is concludes that the proposed algorithm is super in real-time performance

low memory requirement and fit for hardware implementation.

关键词

Keywords

references

PAN H, SIU W C, LAW N F. A fast and low memory image coding algorithm based on lifting wavelet transform and modified SPIHT [J]. Signal Processing: Image Communication, 2008,23(1):146-161.[2] JYOTHESWAR J, MAHAPATRA S. Efficient FPGA implementation of DWT and modified SPIHT for lossless image compression [J]. Journal of Systems Architecture, 2007,53(4):369378.[3] KAVITHA S, MOHAMMED S, ROOMI M, et al.. Lossless compression through segmentation on low depth-of-field images [J]. Digital Signal Processing, 2009,19(1):59-65.[4] ADAMS M D, KOSSENTINI F. Lossless image compression with projection-based and adaptive reversible integer wavelet transforms [J]. IEEE Trans. Image Process, 2003,12(5):489-499.[5] SHAPIRO J M. Embedded image coding using zero-trees of wavelet coefficients [J]. IEEE Trans. Signal Process, 1993, 41(12):3445-3462.[6] SAID A, PEARLMAN W A. A new fast and efficient image codec based on set partitioning in hierarchical trees[J]. IEEE Trans. Circ. Syst. Video Technol, 1996,6(3):243-250.[7] TAUBMAN D. High performance scalable image compression with EBCOT [J]. IEEE Trans. Image Processing, 2000,9(7):1158-1170.[8] 郝燕玲,刘营. 应用于JPEG2000的离散小波变换并行超大规模集成结构[J]. 光学精密工程,2009,17(5):1181-1186. HAO Y L, LIU Y. Parallel VLSI architecture of discrete wavelet transform for JPEG2000 [J]. Opt. Precision Eng.,2009,17(5):1181-1186. (in Chinese)[9] 郑启枣, 刘鹏. 基于线性预测的动态阈值JPEG2000码率控制算法[J]. 浙江大学学报(工学版), 2008, 42(8):1135-1140. ZHENG Q Z, LIU P. Dynamic threshold JPEG2000 rate control algorithm based on linear prediction [J]. Journal of Zhejiang University (Engineering Science), 2008,42(8):1135-1140.(in Chinese)[10] 徐勇,徐智勇,张启衡,等. 适于硬件实现的低复杂度图像压缩[J]. 光学精密工程,2009,17(9):2262-2267. XU Y, XU ZH Y, ZHANG Q H, et al... Low complexity image compression scheme for hardware implementation [J]. Opt. Precision Eng., 2009,17(9):2262-2267. (in Chinese)[11] BRAHIMI T, MELIT A, KHELIFIB F. An improved SPIHT algorithm for lossless image coding [J]. Digital Signal Processing, 2009,19(7):220228.[12] 孙蕾,罗建书,谷德峰. 基于谱间预测和码流预分配的高光谱图像压缩算法[J]. 光学精密工程,2008,16(4):752-757. SUN L, LUO J SH, GU D F. Hyperspectral image compression algorithm based on prediction between bands and rate pre-allocation [J]. Opt. Precision Eng., 2008,16(4):752-757. (in Chinese)

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Compression for UAV reconnaissance images

Image compression algorithm based on adaptive exp-Golomb coding

JPEG2000 compression for remote sensing images with precise quality control

Remote sensing image compression based on fast direction prediction

Lossless compression of hyperspectral images based on contents

Related Author

WANG Yuan-yuan

HUANG Da-qing

SUN Jian1

REN GUO-qiang1

WU QIN-zhang1

SONG Bei-bei

SUN Wen-fang

Related Institution

Electronic Information Engineering College, Nanjing University of Aeronautics and Astronautics

UAV Research Institute, Nanjing University of Aeronautics and Astronautics

Institute of Optics and Electronics, Chinese Academy of Sciences

University of Chinese Academy of Sciences

长安大学信息工程学院

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰