留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

自适应立方卷积图像插值算法

李春龙 潘海侠 王华峰

李春龙, 潘海侠, 王华峰等 . 自适应立方卷积图像插值算法[J]. 北京航空航天大学学报, 2014, 40(10): 1463-1468. doi: 10.13700/j.bh.1001-5965.2013.0621
引用本文: 李春龙, 潘海侠, 王华峰等 . 自适应立方卷积图像插值算法[J]. 北京航空航天大学学报, 2014, 40(10): 1463-1468. doi: 10.13700/j.bh.1001-5965.2013.0621
Li Chunlong, Pan Haixia, Wang Huafenget al. Adaptive cubic convolution based image interpolation approach[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(10): 1463-1468. doi: 10.13700/j.bh.1001-5965.2013.0621(in Chinese)
Citation: Li Chunlong, Pan Haixia, Wang Huafenget al. Adaptive cubic convolution based image interpolation approach[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(10): 1463-1468. doi: 10.13700/j.bh.1001-5965.2013.0621(in Chinese)

自适应立方卷积图像插值算法

doi: 10.13700/j.bh.1001-5965.2013.0621
详细信息
    作者简介:

    李春龙(1988-),男,山西吕梁人,硕士生,lcl426@gmail.com.

  • 中图分类号: TP751

Adaptive cubic convolution based image interpolation approach

  • 摘要: 图像插值是图像处理的一项重要技术,可适用于多个领域,近年来多使用该技术进行图像缩放.针对传统图像缩放算法边缘处理效果较差、边缘检测插值算法复杂度高的问题,提出一种有效增强边缘轮廓的自适应立方卷积插值算法.该算法结合边缘梯度变化和立方卷积插值的特点,使得图像在平坦和纹理区域均能取得理想效果.实验结果表明,与基于边缘检测的插值算法相比,该算法具有较低的复杂度,平均运算时间降低了3.19 s;与立方卷积算法相比,图像峰值信噪比有较大的提高,峰值信噪比增加了0.89 dB.

     

  • [1] Hou H S, Andrews H C.Cubic splines for image interpolation and digital filtering[J].IEEE Transactions on Acoustics,Speech and Signal Processing,1978,26(6):508-517
    [2] Keys R C. Cubic convolution interpolation for digital image processing[J].IEEE Transactions on Acoustics,Speech and Signal Processing,1981,29(6):1153-1160
    [3] Li X, Orchard M T.New edge-directed interpolation[J].IEEE Transactions on Image Processing,2001,10(10):1521-1527
    [4] Zhang X J, Wu X L.Image interpolation by adaptive 2-d autoregressive modeling and soft-decision estimation[J].IEEE Transactions on Image Processing,2008,17(6):887-896
    [5] Chang S G, Cvetkovic Z,Vetterli M.Locally adaptive wavelet-based image interpolation[J].IEEE Transactions on Image Processing,2006,15(7):1471-1485
    [6] 程光权,成礼智. 基于小波的方向自适应图像插值[J].电子与信息学报,2009,31(3):265-272 Cheng Guangquan,Cheng Lizhi.Direction adaptive image interpolation via wavelet transform[J].Journal of Electronics & Information Technology,2009,31(3):265-272(in Chinese)
    [7] Han J W, Kim J H,Cheon S H,et al.A novel image interpolation method using the bilateral filter[J].IEEE Transactions on Consumer Electronics,2010,56(1):175-181
    [8] 孙毓敏. 一种基于融合的方向自适应插值算法及其应用[D].西安:西安电子科技大学,2009 Sun Yumin.A locally orientation-adaptive and fusion-based algorithm for image interpolation[D].Xi' an:Xidian University,2009(in Chinese)
    [9] Zhou D, Shen X,Dong W.Image zooming using directional cubic convolution interpolation[J].IET Image Processing,2012, 6(6): 627-634
    [10] 杨鹤猛, 黄战华.基于梯度的快速图像插值算法[J].计算机应用,2012,32(10):2821-2826 Yang Hemeng,Huang Zhanhua.Fast image interpolation algorithm based on gradient[J].Journal of Computer Applications,2012,32(10):2821-2826(in Chinese)
    [11] Feng X J, Allebach J P.Segmented image interpolation using edge direction and texture synthesis[C]//Proceedings of IEEE International Conference on Image Processing.Piscataway,NJ:IEEE,2008:881-884
    [12] 党向盈,吴锡生, 赵勇.基于边缘最大相关性的快速图像插值算法[J].计算机应用,2006,26(12):2880-2883 Dang Xiangying,Wu Xisheng,Zhao Yong.Fast image interpolation algorithm based on edge-directed max-relativity[J].Computer Applications,2006,26(12):2880-2883(in Chinese)
    [13] Li M, Nguyen T.Markov random field model-based edge-directed image interpolation[J].IEEE Transactions on Image Process,2008,17(7):1121-1128
    [14] 贾小军, 喻擎苍,方玫,等.约束点模型的图像放大方法[J].计算机工程,2008,34(2):232-234 Jia Xiaojun,Yu Qingcang,Fang Mei,et al.Image enlargement method based on constrained points model[J].Computer Engineering,2008,34(2):232-234(in Chinese)

  • 加载中
计量
  • 文章访问数:  1258
  • HTML全文浏览量:  67
  • PDF下载量:  647
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-10-30
  • 网络出版日期:  2014-10-20

目录

    /

    返回文章
    返回
    常见问答