星上大视场TDICCD相机的多光谱图像无损压缩系统

李进; 金龙旭; 李国宁; 韩双丽; 张然峰

doi:10.3788/fgxb20133404.0506

您当前的位置：

首页 >

文章列表页 >

星上大视场TDICCD相机的多光谱图像无损压缩系统

发光学应用及交叉前沿 | 更新时间：2020-08-12

- 星上大视场TDICCD相机的多光谱图像无损压缩系统
- Lossless Compression System of Multi-spectral Image for Spaceborne TDICCD Camera with A Large Field of View
- 发光学报 2013年34卷第4期页码：506-515
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2. 中国科学院大学, 北京 100049
- 作者简介：
- 基金信息：
  
  国家863高技术研究发展计划基金(863-2-5-1-13B)资助项目()
- DOI：10.3788/fgxb20133404.0506
  中图分类号： TP391.4
- 收稿日期：2012-11-29，
  
  修回日期：2013-01-12，
  
  纸质出版日期：2013
- 稿件说明：
移动端阅览
李进, 金龙旭, 李国宁, 韩双丽, 张然峰. 星上大视场TDICCD相机的多光谱图像无损压缩系统[J]. 发光学报, 2013,34(4): 506-515

LI Jin, JIN Long-xu, LI Guo-ning, HAN Shuang-li, ZHANG Ran-feng. Lossless Compression System of Multi-spectral Image for Spaceborne TDICCD Camera with A Large Field of View[J]. Chinese Journal of Luminescence, 2013,34(4): 506-515
李进, 金龙旭, 李国宁, 韩双丽, 张然峰. 星上大视场TDICCD相机的多光谱图像无损压缩系统[J]. 发光学报, 2013,34(4): 506-515 DOI： 10.3788/fgxb20133404.0506.

LI Jin, JIN Long-xu, LI Guo-ning, HAN Shuang-li, ZHANG Ran-feng. Lossless Compression System of Multi-spectral Image for Spaceborne TDICCD Camera with A Large Field of View[J]. Chinese Journal of Luminescence, 2013,34(4): 506-515 DOI： 10.3788/fgxb20133404.0506.

摘要

提出了一种适于成像谱段数相对较少的多光谱TDICCD图像的无损压缩系统。所提出的压缩系统主要分为两步:第一步采用SPE架构的5/3提升整数小波变换去除空间冗余;第二步根据小波系数统计依赖性模型对小波系数进行预测

来消除残余空间冗余和小波系数的谱段冗余。然后将其与预测值做差进而得到预测残差

同时将预测残差进行熵编码得到最终的压缩码流。最后

使用地检检测设备对多光谱TDICCD图像无损压缩系统进行了试验验证。结果表明

压缩系统能快速、可靠稳定地工作

无损压缩比达到1.544 bits/pixel

比现有压缩系统压缩比提高了0.336 bits/pixel。相机工作在不同的侧摆下

压缩系统可以稳定正常地工作

压缩一帧图像最大耗时仅为26.446 ms。本文所提出的压缩系统有效地解决了多光谱TDICCD图像无损压缩比低和压缩算法整体硬件实现困难的问题。

Abstract

A lossless compression system for multi-spectral TDICCD images consisting of few bands is proposed. The compression scheme has two main steps. The first is that a 5/3 integer lifting wavelet transform

which is implemented by proposed SPE structure

is used to reduce spatial correlation. The second is that the wavelet detail coefficients are predicted according to the proposed statistical dependence between the wavelet coefficients to reduce both the inter-bands and remaining intra-band correlation. To output the compressed stream

the predicted residual error is encoded using an entropy coder. Finally

the verification experiments to the lossless compression system of multi-spectral TDICCD images using ground test equipment were carried out. The experiments results showed that the proposed compression system can work fast

reliably and stably. The lossless compression rate is reached 1.544 bits/pixel. Compared with traditional approaches

the proposed method could improve the average compression rate by 0.336 bits/pixel. The compression system can work properly at different sideways. The maximum time of compressing one frame image is only 26.446 ms. It effectively solves the difficult of hardware implementation of the whole wavelet-based compression scheme and improves the average lossless compression rate.

关键词

Keywords

references

Lv H Y, Liu Y, Guo Y F. Computation of overlapping pixels of mechanical assembly CCD focal planes in remote sensing cameras [J]. Opt. Precision Eng.(光学精密工程), 2012, 20(5):1041-1047 (in Chinese).[2] Yang S H, Guo M A, Li B K, et al. Design of digital EMCCD camera with mega pixels [J]. Opt. Precision Eng.(光学精密工程), 2011, 19(12):2970-2976 (in Chinese).[3] Li J, Jin L X, Han SH L, et al. Reliability of space image recorder based on NAND flash memory [J]. Opt. Precision Eng.(光学精密工程), 2012, 20(5):1090-1100 (in Chinese).[4] Mielikainen J. Lossless compression of hyperspectral images using lookup tables [J]. IEEE Signal Processing Lett., 2006, 13(3):157-160.[5] Huang B, Sriraja Y. Lossless compression of hyperspectral imagery via lookup tables with predictor selection [J]. SPIE, 2006, 6365:50L1-1-8.[6] Mielikainen J, Toivanen P. Lossless compression of hyperspectral images using a quantized index to lookup tables [J]. IEEE Geosci.Remote Sens.Letters, 2008, 5(3):474-478.[7] Tian X, Wu L, Tan Y H, et al. Efficient multi-input/multi-output VLSI architecture for two-dimensional lifting-based discrete wavelet transform [J]. IEEE Transactions on Computers, 2011, 60(8):1207-1211.[8] Basant K M, Pramod K M. Memory efficient modular VLSI architecture for high throughput and low-latency implementation of multilevel lifting 2-D DWT [J]. IEEE Transactions on Signal Processing, 2011, 59(5):2072-2084.[9] Zhang W, Jiang Z, Gao Z Y, et al. An efficient VLSI architecture for lifting-based discrete wavelet transform [J]. IEEE Transactions on Circuits and Systems-Ⅱ: Express Briefs, 2012, 59(3):158-162.[10] Crochiere R E, Rabiner L R. Multirate Digital Signal Processing [M]. London: Prentice Hall, 1983.[11] Dunn P F. Measurement and Data Analysis for Engineering and Science [M]. New York: McGraw-Hill, 2005.[12] Rizzo F, Carpentieri B, Motta G, et al. Low complexity lossless compression of hyperspectral imagery via linear prediction [J]. IEEE Signal Processing Letters, 2005, 12(2):138-141.[13] Liu K, Belyaev E, Guo J. VLSI architecture of arithmetic coder used in SPIHT [J]. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2012, 20(4):697-710.[14] Jin Y, Lee H J. A block-based pass-parallel SPIHT algorithm [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2012, 22(7):1064-1075.[15] Jose E S, Estanislau A, Josep S, et al. Review and implementation of the emerging CCSDS recommended standard for multispectral and hyperspectral lossless image coding [C]//IEEE International Conference on Data Compression, Communications and Procession, Barcelona, Spain:IEEE, 2011:222-228.[16] Ruedin A, Dabiel A. A class-conditioned lossless wavelet-based predictive multispectral image compressor [J]. IEEE Geosciences and Remote Sensing Letters, 2010, 7(1):166-170.[17] Fouad K, Ahmed B, Fatih K. Joined spectral trees for scalable SPIHT-based multispectral image compression [J]. IEEE Transactions on Multimedia, 2008, 10(3):316-329.[18] Wang J J, Liu B. Hardware implementation of lossless image compression [J]. Opt. Precision Eng.(光学精密工程), 2011, 19(4):922-928 (in Chinese).

浏览量

154

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

暂无数据