基于JPEG2000压缩域的Web图像检索
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摘要
互联网上存在大量图像信息，如何有效的对图像资源进行组织并检索到用户所需要的图像，便成为人们研究的课题。由于基于压缩域的图像检索能够同时达到检索快速和检索效果良好这两个目的，成为近年来图像工作者的研究热点。压缩技术的多样性，导致基于压缩域的检索技术种类繁多。小波理论近年来得到了广泛关注和较快的发展，它能够对研究对象同时在频率域和时间域上进行分析，能够进行多分辨率分析。经小波变换后产生的小波系数可以很好的体现图像信息的局部特性。这些优点促进了人们对基于离散小波变换域的图像搜索技术的研究。新一代压缩标准JPEG2000采用小波变换技术，由于该标准所具有的各种优点，使得这种图像压缩标准会逐渐在Internet、医学、地质和数码产品等各个领域得到应用和普及。于是更显示了研究基于小波域图像检索技术的重要性，但到目前为止专门针对JPEG2000压缩域的图像检索算法很少，国内关于这方面的文章也很少，有限的几个算法检索效率也不高。所以为了适应对网络上海量图像快速搜索的需要以及JPEG2000新标准的推出，本文提出了两种改进了的基于JPEG2000压缩域的图像搜索算法。
本文首先对小波理论进行了一定的阐述，并详细说明了使用此技术对图像进行处理的天然优势，包括多分辨率分析和嵌入式编码。随后对
There are abundant of image information on Internet. How to manage the image resources efficiently and search the images that users need is becoming the people's researching topics. Because the image indexing based on compressed domain can attain the two objects of quick retrieval speed and good retrieval result at the same time, it has already been the research hotspot in recent years. The diversity of compression technologies leads to the diversity of searching technologies. Wavelet theory has been received broad attention and quick development. It could analyse the researching object on frequency domain and time domain concurrently and has multi-resolution analyse ability. The coefficients after wavelet transform could embody the part features of image information perfectly. These advantages promote people to study the image searching based on discrete wavelet transform domain. The new compression standard JPEG2000 adopts wavelet transform technology. Because of the priorities of the convention, it could be applied broadly on Internet, medicine, geology and data products. So it's very important to research the technologies about
本文首先对小波理论进行了一定的阐述，并详细说明了使用此技术对图像进行处理的天然优势，包括多分辨率分析和嵌入式编码。随后对
There are abundant of image information on Internet. How to manage the image resources efficiently and search the images that users need is becoming the people's researching topics. Because the image indexing based on compressed domain can attain the two objects of quick retrieval speed and good retrieval result at the same time, it has already been the research hotspot in recent years. The diversity of compression technologies leads to the diversity of searching technologies. Wavelet theory has been received broad attention and quick development. It could analyse the researching object on frequency domain and time domain concurrently and has multi-resolution analyse ability. The coefficients after wavelet transform could embody the part features of image information perfectly. These advantages promote people to study the image searching based on discrete wavelet transform domain. The new compression standard JPEG2000 adopts wavelet transform technology. Because of the priorities of the convention, it could be applied broadly on Internet, medicine, geology and data products. So it's very important to research the technologies about
引文
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[3] Liu Chuping. Image Indexing in the Embedded Wavelet Domain [Dissertation] Edmonton, Alberta. University of Alberta (2002)
[4] 张旭东，卢国栋，冯健。图像编码基础和小波压缩技术—原理、算法和标准，北京，清华大学出版社(2004)，165-168
[5] http://www.bearcave.com/misl/misl_tech/wavelets/daubechies/
[6] 徐险峰。基于Web的互联网图像信息搜索引擎研究，现代情报，2004(5)，72-74
[7] 刘伟成，孙吉红。基于内容的图像信息检索综述，情报科学，2001，20(4)，431-433，437
[8] 郑爱彬。基于相关聚合直方图的图像检索研究，[学位论文]，南京师范大学，2003
[9] 董卫军，陈吉，周明全。利用小波分析进行基于形状的图像检索技术，西北大学学报，2004(34)，271-274
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[13] Celentano A, Lecce V D. AFFT-based technique for image signature generation, In: Proceedings of SPIE: Storage and Retrieval for Image and Video Database, San Jose,??1997, 457-466
[14] Augusteijn M, Clemens L E, Shaw K A. Performance evaluation of texture measure for ground cover identification in satellite images by means of a neural network classifier, IEEE Transactions on Geoscience & Remote Sensing, 1995, 33(3), 616-626
[15] Pentland A. Photobook: Tools for content-based manipulation of image database, In: Proceedings of SPIE: Storage and Retrieval for Image and Video, Database, San Jose, 1994, 34-47
[16] Swets D L, Weng J. Using discriminant eigen feature for image retrieval, IEEE Transactions on Pattem Analysis and Machine Intelligence, 1996, 18(8), 831-836
[17] Feng Guocan, Jiang Jianmin. JPEG compressed image retrieval via statistical features Pattern Recognition, 36(2003), 977-985
[18] Jacobs C E etal. Fast multi resolution image querying, In: ACM International conference on Computer graphics and interactive techniques, Los Angeles, 1995, 277-286
[19] 李晓华，沈兰荪。基于压缩域的图像检索技术。计算机学报，2003，26(9)，1051-1059
[20] 傅蓉，许宏丽。基于小波多尺度分析的彩色图像检索方法，中国图象图形学报，2004，9(11)，1326-1330
[21] 倪林，苗原。一种JPEG2000压缩域图像检索方法，电子与信息学报，2005，27(3)，474-477
[22] 魏海，沈兰荪。量化方法及其统计特征量用于图像检索的性能比较，电路与系统学报，2001(3)，11-15
[23] Salomon David[美]。吴乐南 等译，数据压缩原理与应用(第二版)，北京电子工业出版社，2003
[24] 谢幸芝。JPEG2000于多重描述传送系统之应用，[学位论文]，台湾，私立中原大学，2001
[25] 小野定康，铃木纯司[日]。强增福译，JPEG2000技术，科学出版社，(2004．4)
[26] C A Christopoulos, T Ebrahimi, A N Skodras. JPEG2000: The New Still Picture??Compression Standard ACM Multimedia Workshop Marina Del Rey CA USA ACM, 2000, 45-49
[27] Impoco Gaetano. JPEG2000 - A Short Tutorial, (2004.4), ISO/IEC
[28] CD15444-1 Information Technology-JPEG2000 Image Coding System, JPEG2000 committee draft, version 1.0, 1999
[29] http://bit.kuas.edu.tw/～x/seminar/20031210.ppt
[30] 孙宁。网络环境下基于内容图像检索工具的研究与实现，[学位论文]，大庆石油学院，2003
[2] 黄翔宇，章毓晋。基于压缩域的图像检索技术研究进展，中国图像图形学报，2003，8(5)，499-508
[3] Liu Chuping. Image Indexing in the Embedded Wavelet Domain [Dissertation] Edmonton, Alberta. University of Alberta (2002)
[4] 张旭东，卢国栋，冯健。图像编码基础和小波压缩技术—原理、算法和标准，北京，清华大学出版社(2004)，165-168
[5] http://www.bearcave.com/misl/misl_tech/wavelets/daubechies/
[6] 徐险峰。基于Web的互联网图像信息搜索引擎研究，现代情报，2004(5)，72-74
[7] 刘伟成，孙吉红。基于内容的图像信息检索综述，情报科学，2001，20(4)，431-433，437
[8] 郑爱彬。基于相关聚合直方图的图像检索研究，[学位论文]，南京师范大学，2003
[9] 董卫军，陈吉，周明全。利用小波分析进行基于形状的图像检索技术，西北大学学报，2004(34)，271-274
[10] J R Smith, S F Chang. Transform features for texture classification and discrimination in large image database[C], In:Proc IEEE Int Conf on Image Proc, 1994
[11] Ma W Y, Manjunath B S. Texture feature and learning similarity[C], In: Proc of IEEE Conf on Computer Vision and Pattern Recognition, Seatle, Washionton. 1996.425-430
[12] Stone H S, Li C S. Image matching by means of intensity and texture matching in the Fourier domain, In: Proceedings of SPIE: Storage and Retrieval for Still Image and Video Database, San Jose, 1996, 337-349
[13] Celentano A, Lecce V D. AFFT-based technique for image signature generation, In: Proceedings of SPIE: Storage and Retrieval for Image and Video Database, San Jose,??1997, 457-466
[14] Augusteijn M, Clemens L E, Shaw K A. Performance evaluation of texture measure for ground cover identification in satellite images by means of a neural network classifier, IEEE Transactions on Geoscience & Remote Sensing, 1995, 33(3), 616-626
[15] Pentland A. Photobook: Tools for content-based manipulation of image database, In: Proceedings of SPIE: Storage and Retrieval for Image and Video, Database, San Jose, 1994, 34-47
[16] Swets D L, Weng J. Using discriminant eigen feature for image retrieval, IEEE Transactions on Pattem Analysis and Machine Intelligence, 1996, 18(8), 831-836
[17] Feng Guocan, Jiang Jianmin. JPEG compressed image retrieval via statistical features Pattern Recognition, 36(2003), 977-985
[18] Jacobs C E etal. Fast multi resolution image querying, In: ACM International conference on Computer graphics and interactive techniques, Los Angeles, 1995, 277-286
[19] 李晓华，沈兰荪。基于压缩域的图像检索技术。计算机学报，2003，26(9)，1051-1059
[20] 傅蓉，许宏丽。基于小波多尺度分析的彩色图像检索方法，中国图象图形学报，2004，9(11)，1326-1330
[21] 倪林，苗原。一种JPEG2000压缩域图像检索方法，电子与信息学报，2005，27(3)，474-477
[22] 魏海，沈兰荪。量化方法及其统计特征量用于图像检索的性能比较，电路与系统学报，2001(3)，11-15
[23] Salomon David[美]。吴乐南 等译，数据压缩原理与应用(第二版)，北京电子工业出版社，2003
[24] 谢幸芝。JPEG2000于多重描述传送系统之应用，[学位论文]，台湾，私立中原大学，2001
[25] 小野定康，铃木纯司[日]。强增福译，JPEG2000技术，科学出版社，(2004．4)
[26] C A Christopoulos, T Ebrahimi, A N Skodras. JPEG2000: The New Still Picture??Compression Standard ACM Multimedia Workshop Marina Del Rey CA USA ACM, 2000, 45-49
[27] Impoco Gaetano. JPEG2000 - A Short Tutorial, (2004.4), ISO/IEC
[28] CD15444-1 Information Technology-JPEG2000 Image Coding System, JPEG2000 committee draft, version 1.0, 1999
[29] http://bit.kuas.edu.tw/～x/seminar/20031210.ppt
[30] 孙宁。网络环境下基于内容图像检索工具的研究与实现，[学位论文]，大庆石油学院，2003
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