低码率下任意形状感兴趣区域编码

杨晓; 杨学友; 叶声华

doi:10.3788/OPE.20122004.0896

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低码率下任意形状感兴趣区域编码

信息科学 | 更新时间：2020-08-12

- 低码率下任意形状感兴趣区域编码
- Arbitrary shape ROI image encoding at low bit rate
- 光学精密工程 2012年20卷第4期页码：896-905
- 作者机构：
  
  天津大学精密测试技术及仪器国家重点实验室天津,300072
- 作者简介：
- 基金信息：
  
  国家自然科学基金重点项目(No.50735003),国家自然科学基金资助项目(No.50705065)()
- DOI：10.3788/OPE.20122004.0896
  中图分类号： TN919.8
- 收稿日期：2011-12-28，
  
  修回日期：2012-02-04，
  
  网络出版日期：2012-04-22，
  
  纸质出版日期：2012-04-22
- 稿件说明：
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杨晓, 杨学友, 叶声华. 低码率下任意形状感兴趣区域编码[J]. 光学精密工程, 2012,(4): 896-905

YANG Xiao, YANG Xue-you, YE Sheng-hua. Arbitrary shape ROI image encoding at low bit rate[J]. Editorial Office of Optics and Precision Engineering, 2012,(4): 896-905
杨晓, 杨学友, 叶声华. 低码率下任意形状感兴趣区域编码[J]. 光学精密工程, 2012,(4): 896-905 DOI： 10.3788/OPE.20122004.0896.

YANG Xiao, YANG Xue-you, YE Sheng-hua. Arbitrary shape ROI image encoding at low bit rate[J]. Editorial Office of Optics and Precision Engineering, 2012,(4): 896-905 DOI： 10.3788/OPE.20122004.0896.

摘要

针对任意形状感兴趣区域(ROI)编码算法在低码率下ROI重建质量差、编码时间长等问题

在优化的集合分裂树算法(SPIHT)基础上提出了一种适用于低码率的任意形状ROI编码方法。利用小波系数之间的空间位置相似性和所用小波滤波器的特征

以极少的码率实现了任意形状ROI掩模的描述

为提高算法效率奠定了基础;利用改进后的空间方向树结构以集合的形式测试ROI区域中更多的节点

提高了SPIHT中分类排序的扫描效率;以小波子带为单位的量化方法通过为每个小波子带选择合适的量化阈值优化了码流的输出

提高了低码率下ROI的重建质量。实验表明

提出的方法支持对多个任意形状ROI的编码;在不到0.04 bit/pixel的码率下描述出了整幅图像中任意形状ROI的掩模信息;在码率小于0.5 bit/pixel时

ROI的峰值信噪比(PSNR)比基于JPEG2000的多子带位平面平移(MSBShift)方法提高了2~7 dB

编码时间缩短了30%以上。该方法具有ROI的重建质量高、编码速度快等特点

适于在低码率下应用。

Abstract

An arbitrary shape ROI coding method based on modified Set Partitioning in Hierarchical trees (SPIHTs) is proposed to solve the problems of arbitrary shape Region of Interest(ROI) coding algorithms in low reconstructed image quality and inefficiency at a low bit rate. The ROI mask is described by combining the similarity of spatial position among wavelet coefficients with the specific wavelet filter at an extremely low bit rate

which lays a foundation for improving coding efficiency. The modified SPIHT partitioning structure is used to improve the coding efficiency of sorting pass by grouping more ROI entries together. A quantization method based on each wavelet subband optimizes the output bit stream in ROI encoding and improves the reconstructed image quality by choosing the proper threshold for each subband. Experiment results show that the proposed method can support multiple arbitrary shape ROIs and can describe the ROI mask information of the whole image at very low bit rate (less than 0.04 bit/pixel). Furthermore

at the bit rate less than 0.5 bit/pixel

the proposed algorithm has improved its Peak Signal to Noise Ratio(PSNR) by 2-7dB

and reduced the encoding time above 30% as compared with those of Multiple Subband Bitplane Shift (MSBShift) algorithm based on JPEG2000. It is concluded that the proposed method has higher reconstructed image quality

faster coding speed and is fit for image application at the low bit rate.

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references

隋玉萍,何昕,魏仲慧. ROI的海洋监测卫星遥感图像压缩算法[J]. 光学精密工程,2008,16(7):1223-1229. SUI Y P, HE X, WEI Z H. A compression algorithm of remote sensing image based on ROI for ocean surveillance satellite [J]. Opt. Precision Eng., 2008, 16(7):1223-1229. (in Chinese)[2] JOAN B R, JOAN S S, FRANCESC A L. JPEG2000 ROI coding through component priority for digital mammography [J].Computer Vision and Image Understanding, 2011,115(1):59-68.[3] 徐勇,徐智勇,张启衡. 基于游程和扩展指数哥伦布编码的任意形状感兴趣区域图像编码[J]. 光学精密工程,2011,19(1):175-181. XU Y, XU Z Y, ZHANG Q H. Arbitrary shaped ROI image coding using Run-length coding and generalized Exp-Golomb coding [J]. Opt. Precision Eng., 2011,19(1):175-181. (in Chinese)[4] PABLO G T, J. R V, MAIA J L, et al.. Image compression: maxshift ROI encoding options in JPEG2000 [J]. Computer Vision and Image Understanding, 2008,109(2):139-145.[5] ZHANG Y, GU H M. Region of interest image coding based on perceptually optimized bitplane realignment. 2009 International Conference on Electronic Computer Technology, Macau, P.R.China: IEEE, 2009:495-498.[6] 张立保,余先川. 基于多子带位平面偏移的遥感图像感兴趣编码[J]. 光学学报,2009,29(12):189-192. ZHANG L B, YU X C. Region of interest coding of remote sensing image based on multiple subband bitplane shift [J]. Acta Optica Sinica, 2009,29(12):189-192. (in Chinese)[7] JOAN B R, JOAN S S, FRANCESC A L. JPEG2000 ROI coding with fine-grain accuracy though rate-distortion optimization techniques [J]. IEEE Signal Processing Letters, 2009,16(1):45-48.[8] OSCAL T C, CHEN C C. Automatically-determined region of interest in JPEG2000 [J]. IEEE Transactions on Multimedia, 2007, 9(7):1333-1344.[9] PUJA B, SAVITA G, RAJKUMARI B. Comparative analysis of image compression techniques: a case study on medical images. 2009 International Conferences on Advances in Recent Technologies in Communication and Computing, Kottayam, India: IEEE, 2009:820-822.[10] 李靖,杨帆,吴涛. 基于背景位平面向低位位移的ROI压缩算法研究[J]. 光电子·激光,2010,21(2):307-311. LI J, YANG F, WU T. The research of the ROI compression algorithm based on the shift background toward the lower bit-plane [J]. Journal of Optoelectronics·Laser, 2010,21(2):307-311. (in Chinese)[11] 王晓东,刘文耀,朱昊,等. 无链表SPIHT图像提升小波编码的硬件算法[J]. 西南交通大学学报,2005,40(4):492-495. WANG X D, LIU W Y, ZHU H, et al.. Listless SPIHT image coding hardware algorithm based on lifting wavelet [J]. Journal of Southwest Jiaotong University, 2005,40(4):492-495. (in Chinese)[12] IMAD Z, IKHIAS A Q, HAZEM A O. Embedded ROI coding of mammograms via combined SPIHT and integer wavelet transforms. 2007 IEEE International Conference on Electro/Information Technology, Chicago IL, U.S.A.: IEEE, 2007:173-177. [13] HU M, ZHANG C J, LU J, et al.. A multi-ROIs medical image compression algorithm with edge feature preserving. Proceedings 2008 3rd International Conference on Intelligent System and Knowledge Engineering, Xiamen, P.R.China: IEEE, 2008:1075-1080.[14] GALAN J C, ALARCON A V, STAROSTENKO O, et al.. Foveated ROI compression with hierarchical trees for real-time video transmission. The 3rd Mexican Conference on Pattern Recognition, Cancun, Mexico: Springer, 2011:240-249.[15] CHEN X L, ZHANG A H, YANG X Z. Multiple description coding for protecting regions of interest in images. 2010 3rd International Congress on Image and Signal Processing, Yantai, P.R.China: IEEE, 2010:544-547.[16] PARK K H, PARK H W. Region of interest coding based on set partitioning in hierarchical trees [J]. IEEE Transactions On Circuits and Systems For Video Technology, 2002, 12(2):106-112.[17] 李晓梅.基于小波变换的医学图像压缩技术的研究. 济南:山东大学,2009. LI X M. Research on medical image compression techniques based on wavelet transform . Jinan:University of Shandong, 2009. (in Chinese)[18] 徐平,朱善安. 基于ISA-DWT的多个任意形状感兴趣区域编码框架[J]. 中国图象图形学报,2006,11(10):1426-1430. XU P, ZHU S A. Multiple arbitrary shape ROIs coding framework using ISA-DWT [J]. Journal of Image and Graphics, 2006,11(10):1426-1430. (in Chinese)

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