多通道航天相机内部的图像实时合成压缩

doi:10.7964/jdxbgxb201306039

摘要/Abstract

摘要：

提出了一种基于FPGA(Field programmable gate array)平台实现的星上时间延时积分电荷耦合器件(Time delay integrate charge coupled device,TDICCD)遥感图像实时合成压缩方法。首先,在信号的处理流程上进行创新。然后,针对TDICCD线阵推扫成像模式的特点,采用一种改进的、无需训练的、基于LMS(Least mean square)的自适应预测编码方法进行合成压缩。最后进行试验验证,结果表明:本文算法在对图像进行无损压缩和2倍压缩时,系统主时钟从110 MHz分别降低为80 MHz和60 MHz,恢复图像的PSNR (Peak signal-to-noise ratio)至84 dB以上;处理每行的平均时间为57.3 μs,小于相机的最小行周期63 μs,满足实时性要求。

关键词: 信息处理技术, 实时合成压缩, 自适应预测, 推扫式遥感相机

Abstract:

In order to solve the problem of imaging system instability caused by high work frequency of the image composing circuit on the satellite, the camera structure was innovated. A composing and compression method of time delay integrate charge coupled device (TDICCD) based on field programmable gate array (FPGA) platform for satellite remote sensing data was proposed. First, the signal flow was improved. Then, based on TDICCD linear array push-broom imaging mode characteristics, an improved predictive code method based on least mean square (LMS) was used for composing and compression. Finally, experiments were conducted on a platform to validate the proposed method. Experimental results indicate that the system clock is reduced to 80 MHz and 60 MHz, respectively, from the original 110MHz in the lossless and 2 times compression. The peak signal-to-noise ratio (PSNR) of the reconstructed image is bigger than 84 dB;the average processing time of one line image is 57.3 μs, which is smaller than camera's smallest line period. The proposed algorithm is stable and it can achieve the composing and compression of multi-channel TDICCD remote image within the camera.

Key words: information processing technology, real-time composing and compression, self-adaptive prediction, push-broom remote-sensing camera

中图分类号:

TP751

刘春香, 郭永飞, 李宁, 薛旭成, 吕恒毅. 多通道航天相机内部的图像实时合成压缩[J]. 吉林大学学报(工学版), 2013, 43(06): 1680-1684.

LIU Chun-xiang, GUO Yong-fei, LI Ning, XUE Xu-cheng, LYU Heng-yi. Real-time composing and compression of image within multi-channel spaceborne camera[J]. 吉林大学学报(工学版), 2013, 43(06): 1680-1684.

参考文献

[1] 张学全. 基于FPGA的星载图像压缩系统实现方法研究[D]. 北京:中国科学院空间科学与应用研究中心, 2009:13-26. Zhang Xue-quan. Implementation of onboard image compression system using FPGA[D]. Beijing:Center for Space Science and Applied Research,Chinese Academy of Sciences:2009:13-26.

[2] Wang Chao, Wu Zhi-lin, Cao Peng, et al. An efficient VLSI architecture for lifting-based discrete wavelet transform[C]//ICME Proceedings, Beijing, China, 2007:1575-1578.

[3] 高婷,吴成柯,王柯俨,等. JPEG2000中一种EBCOT并行体系的研究[J]. 空间电子技术,2010(1):70-73. Gao Ting, Wu Cheng-ke, Wang Ke-yan,et al. A parallel coder for EBCOT in JPEG2000[J]. Space Electronic Technology, 2010(1): 70-73.

[4] 桑爱军杨树媛赵欣. 基于多维矢量矩阵离散余弦变换的熵编码[J]. 吉林大学学报:工学版,2011,41(增刊1):319-324. Sang Ai-jun, Yang Shu-yuan, Zhao Xin. Entropy code based on multidimensional vector matrix DCT[J]. Journal of Jiin University (Engineering and Technology Edition), 2011,41(Sup.1):319-324.

[5] 丁媛媛,司玉娟,郎六琪,等. 基于提升小波变换的图像压缩编码的VLSI实现[J]. 吉林大学学报:工学版,2007,37(3):675-680. Ding Yuan-yuan, Si Yu-juan, Lang Liu-qi, et al. VLSI implementation of image compression coding based on lifting wavelet transform[J]. Journal of Jilin University(Engineering and Technology Edition), 2007, 37(3): 675-680.

[6] Papadonikolakis M E, Kakarountas A P. Efficient high-performance implementation of JPEG-LS encoder[J]. Journal of Real-time Image, 2008(3): 303-310.

[7] 沈洪亮,刘金国. 基于JPEG-LS的遥感图像无损压缩技术[J]. 光电子技术,2009,29(3):206-210. Shen Hong-liang, Liu Jin-guo. Lossless image compression of remote sensing images base on the JPEG-LS[J]. Optoelectronic Technology, 2009,29(3): 206-210.

[8] 吴乐南. 数据压缩[M]. 北京:电子工业出版社,2005:90-93.

[9] Zhang Xiao-yu, Cheng Xin-kai, Li Xiao-wen, et al. Key optimization techniques in JPEG-LS IP core design[J]. Journal of Electronics, 2010,27(1):94-98.

[10] Ameer S, Basir O. Image compression using plane fitting with inter-block prediction[J]. Image and Vision Computing, 2009,27(4):385-390.

[11] 雒江涛,杨叶,舒忠玲,等.WAP彩信业务多层数据重组和图像重建方法[J].重庆邮电大学学报:自然科学版,2012,24(2):178-184. Luo Jiang-tao,Yang Ye,Shu Zhong-ling,et al. Method of the multi-layer data reassembly and image reconstruction for WAP multi-media message service[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition),2012,24(2):178-184.

[12] 肖化超,周诠. 基于LMS的图像自适应预测编码[J]. 电子设计工程,2011,19(4):109-112. Xiao Hua-chao, Zhou Quan. Adaptive prediction image coding based on LMS aigorithm[J]. Electronic Design Engineering, 2011, 19(4):109-112.

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