[1]崔春惠 张桂玲 张大坤.图像容错技术研究[J].计算机技术与发展,2011,(03):15-19.
 CUI Chun-hui,ZHANG Gui-ling,ZHANG Da-kun.A Survey on Image Fault Tolerance Technology[J].,2011,(03):15-19.
点击复制

图像容错技术研究()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2011年03期
页码:
15-19
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
A Survey on Image Fault Tolerance Technology
文章编号:
1673-629X(2011)03-0015-05
作者:
崔春惠 张桂玲 张大坤
天津工业大学计算机科学与软件学院
Author(s):
CUI Chun-hui ZHANG Gui-ling ZHANG Da-kun
School of Computer Science & Software Engineering, Tianjin Polytechnic University
关键词:
网络传输图像容错JPEG2000
Keywords:
network transfer image fault tolerance JPEG2000
分类号:
TP391.41
文献标志码:
A
摘要:
近年来,随着互联网及通信技术的飞速发展,数字图像等各种数据在网络中的传输更加广泛,人们对图像数据在网络中传输的鲁棒性的要求也越来越高,图像容错技术正是提高这一鲁棒性的重要手段之一。对容错相关技术进行了介绍,对现有图像容错方法进行了研究,分析了各种方法的优缺点。JPEG2000是一种新颖的图像压缩标准,分析了JP2文件及JPEG2000码流的结构特点,重点对各种基于JPEG2000标准的图像在网络传输中的容错算法进行了分析和比较,阐明各种算法的优缺点
Abstract:
In recent years, network and communication technology have developed rapidly, and transfer robustness of image data on the network is becoming more and more important. Image fault tolerance technology is one of key measures for improving the robustness. Advantages and deficiencies of currently existing image fault tolerance algorithms are analyzed and compared, and the development trend of image fault tolerance technology is discussed. Then JPEG2000 based fault resilience algorithms for image transmission on network are investigated particularly. Advantages and deficiencies of each algorithm are presented after analyzing and comparing the performance of these methods

相似文献/References:

[1]吴长勤 段汉根.基于灰色预测的残缺图像的修复算法[J].计算机技术与发展,2010,(05):124.
 WU Chang-qin,DUAN Han-gen.An Algorithm for Image Reparation Based on Grey Prediction[J].,2010,(03):124.
[2]王兴武 章权兵 徐颜.基于SOA机场防入侵系统的研究[J].计算机技术与发展,2009,(10):152.
 WANG Xing-wu,ZHANG Ouan-bing,XU Yah.Research of Airport Anti - Intrusion System Based on SOA Architecture[J].,2009,(03):152.
[3]陈帅 钟先信 朱士永 石军锋.基于线性同余的伪随机序列图像加密[J].计算机技术与发展,2006,(04):17.
 CHEN Shuai,ZHONG Xian-xin,ZHU Shi-yong,et al.Image Encryption Through Pseudo- Random Sequence Based on Linear Congruence[J].,2006,(03):17.
[4]袁玲 杜启亮.细胞位姿视觉识别的研究[J].计算机技术与发展,2011,(12):89.
 YUAN Ling,DU Qi-Hang.Research on Cell's Position-Orientation Identification[J].,2011,(03):89.
[5]王柏 胡谷雨 罗健欣.数字地球系统中海量数据存储与传输方案研究[J].计算机技术与发展,2012,(03):81.
 WANG Bai,HU Gu-yu,LUO Jian-xin.Research of Massive Data Storage and Transmission for Digital Earth System[J].,2012,(03):81.
[6]侯艳丽.融合多特征的纹理图像分割算法[J].计算机技术与发展,2012,(05):120.
 HOU Yan-li.Texture Image Segmentation Algorithm of Space Feature and Frequency Feature Fusion[J].,2012,(03):120.
[7]俞文静,张明军,王影.面向视频超分辨率重建的混合粒子群优化算法[J].计算机技术与发展,2018,28(11):75.[doi:10.3969/ j. issn.1673-629X.2018.11.017]
 YU Wen-jing,ZHANG Ming-jun,WANG Ying.A Hybrid Particle Swarm Optimization Algorithm for Image/ Video Super-resolution Reconstructio[J].,2018,28(03):75.[doi:10.3969/ j. issn.1673-629X.2018.11.017]
[8]陆兴华,王凌丰,曾世豪,等.基于神经网络学习的多姿态人脸图像识别算法[J].计算机技术与发展,2019,29(11):57.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 012]
 LU Xing-hua,WANG Ling-feng,ZENG Shi-hao,et al.Multi-pose Face Image Recognition Algorithm Based on Neural Network Learning[J].,2019,29(03):57.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 012]
[9]陆兴华,蔡 韬.基于 CNN 的安防监控步态特征提取研究[J].计算机技术与发展,2019,29(11):123.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 025]
 LU Xing-hua,CAI Tao.Research on Gait Feature Extraction in Security Monitoring System Based on CNN[J].,2019,29(03):123.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 025]

备注/Memo

备注/Memo:
天津市“十一五”重点投资人才引进计划(029416)崔春惠(1986-),女,硕士研究生,研究方向为图像处理;张桂玲,教授,博士,CCF会员,研究方向为图像处理等;张大坤,教授,博士,研究方向为图像处理、组合算法设计等
更新日期/Last Update: 1900-01-01