高级搜索

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

基于图像分块和优化累积能量图的线裁剪算法

郭迎春 梁云鹤 于明 张婷婷

郭迎春, 梁云鹤, 于明, 张婷婷. 基于图像分块和优化累积能量图的线裁剪算法[J]. 电子与信息学报, 2018, 40(2): 331-337. doi: 10.11999/JEIT170501
引用本文: 郭迎春, 梁云鹤, 于明, 张婷婷. 基于图像分块和优化累积能量图的线裁剪算法[J]. 电子与信息学报, 2018, 40(2): 331-337. doi: 10.11999/JEIT170501
An Improved Seam Carving Algorithm Based on Image Blocking and Optimized Cumulative Energy Map[J]. Journal of Electronics & Information Technology, 2018, 40(2): 331-337. doi: 10.11999/JEIT170501
Citation: An Improved Seam Carving Algorithm Based on Image Blocking and Optimized Cumulative Energy Map[J]. Journal of Electronics & Information Technology, 2018, 40(2): 331-337. doi: 10.11999/JEIT170501

基于图像分块和优化累积能量图的线裁剪算法

doi: 10.11999/JEIT170501
基金项目: 

国家自然科学基金(60302018),天津市科技计划项目(14RCGFGX00846, 15ZCZDNC00130),河北省自然科学基金面上项目(F2015202239)

An Improved Seam Carving Algorithm Based on Image Blocking and Optimized Cumulative Energy Map

Funds: 

The National Natural Science Foundation of China (60302018), The Sci-tech Planning Projects Foundation of Tianjin (14RCGFGX00846, 15ZCZDNC00130), The Natural Science Foundation of Hebei Province (F2015202239)

  • 摘要: 针对传统线裁剪方法对图像过度裁剪造成失真的问题,该文提出一种基于图像分块的线裁剪方法。该方法把分块的思想融入到线裁剪并优化累积能量图,能在一定程度上保护图像主体区域,又兼顾背景区域的裁剪效果。分块是根据显著图的平均列累加能量向量按照逐列标记的方式把图像分成保护区域和非保护区域,再根据每个区域的面积来分配裁剪线的数目。在裁剪过程中,优化了累积能量图,降低了小面积显著主体被裁剪掉的可能性。在MSRA数据库上与目前流行的线裁剪及其改进的方法进行对比,并把各种方法得到的缩放结果图在互联网上进行主观评价测试,实验结果表明该文方法具有更好的主观缩放效果,对各类图像的缩放具有普适性。
  • THVENAZ P, BLU T, and UNSER M. Interpolation revisited [medical images application][J]. IEEE Transactions on Medical Imaging, 2000, 19(7): 739-758. doi: 10.1109/42. 875199.
    SURESHA D and PRAKASH H N. Single picture super resolution of natural images using N-Neighbor Adaptive Bilinear Interpolation and absolute asymmetry based wavelet hard thresholding[C]. 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, Bangalore, India, 2016: 387-393.
    肖志涛, 冯铁君, 张芳, 等. 基于角点保护的偏微分方程图像插值方法[J]. 电子与信息学报, 2015, 37(8): 1892-1899. doi: 10.11999/JEIT141420.
    XIAO Zhitao, FENG Tiejun, ZHANG Fang, et al. Image interpolation with corner preserving based on partial differential equation[J]. Journal of Electronics Information Technology, 2015, 37(8): 1892-1899. doi: 10.11999/JEIT 141420.
    CHEN Y L, HUANG T W, CHANG K H, et al. Quantitative analysis of automatic image cropping algorithms: A dataset and comparative study[C]. IEEE Conference on Applications of Computer Vision, Santa Rosa, CA, USA, 2017: 226-234.
    CHEN Jiansheng, BAI Gaocheng, LIANG Shaoheng, et al. Automatic image cropping: A computational complexity study[C]. IEEE Computer Vision and Pattern Recognition, Las Vegas, NV, USA, 2016: 507-515.
    AVIDAN S and SHAMIR A. Seam carving for content-aware image resizing[J]. ACM Transactions on Graphics, 2007, 26(3): 101-109. doi: 10.1145/1275808.1276390.
    聂栋栋, 马勤勇, 马利庄. 基于梯度矢量方向性分析的线裁剪算法[J]. 电子与信息学报, 2012, 34(6): 1506-1510. doi: 10.3724/SP.J.1146.2011.01171.
    NIE Dongdong, MA Qinyong, and MA Lizhuang. Seam carving algorithm based on gradient vector direction analysis [J]. Journal of Electronics Information Technology, 2012, 34(6): 1506-1510. doi: 10.3724/SP.J.1146.2011.01171.
    RAZ G, SHMUELI R, and KATZ E. Texture segmentation for seam carving[C]. IEEE Conference on Science of Electrical Engineering, Eilat, Israel, 2017: 1-5.
    MANSFIELD A, GEHLER P, VAN GOOL L, et al. Scene carving: Scene consistent image retargeting[C]. European Conference on Computer Vision, Heraklion, Crete, Greece, 2010: 143-156.
    DOMINGUES D, ALAHI A, and VANDERGHEYNST P. Stream carving: An adaptive seam carving algorithm[C]. IEEE International Conference on Image Processing, Hong Kong, China, 2010: 901-904.
    AGHCHEHKOHAL M G and KUMARA W G C W. Improved seam carving using meta-heuristics algorithms combination[C]. IEEE Signal Processing and Intelligent Systems Conference, Tehran, Iran, 2015: 43-47.
    LIN Xiao, SHENG Bin, MA Lizhuang, et al. Seamlet carving for shape-aware image resizing[J]. Science China Information Sciences, 2012, 55(5): 1073-1081. doi: 10.1007/s11432-012- 4565-z.
    ZHOU Bin, WANG Xuanyin, CAO Songxiao, et al. Optimal bi-directional seam carving for compressibility-aware image retargeting[J]. Journal of Visual Communication Image Representation, 2016, 41: 21-30. doi: 10.1016/j.jvcir.2016.09. 002.
    SHAFIEYAN F, KARIMI N, MIRMAHBOUB B, et al. Image retargeting using depth assisted saliency map[J]. Image Communication, 2016, 50(C): 34-43. doi: 10.1016/j. image.2016.10.006.
    赵旦峰, 王博, 杨大伟. 基于随机置乱的内容感知图像缩放算法[J]. 吉林大学学报(工学版), 2015, 45(4): 1324-1328. doi: 10. 13229/j.cnki.jdxbgxb201504043.
    ZHAO Danfeng, WANG Bo, and YANG Dawei. Content- aware image based on radom permutation[J]. Journal of Jilin University (Engineering and Technology Edition), 2015, 45(4): 1324-1328. doi: 10.13229/j.cnki. jdxbgxb201504043.
    ZHU Wangjiang, LIANG Shuang, WEI Yichen, et al. Saliency optimization from robust background detection[C]. IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA, 2014: 2814-2821.
  • 加载中
计量
  • 文章访问数:  1357
  • HTML全文浏览量:  162
  • PDF下载量:  302
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-05-24
  • 修回日期:  2017-10-13
  • 刊出日期:  2018-02-19

目录

    /

    返回文章
    返回