Image super-resolution based on image adaptive decomposition

被引:0
作者
Xie, Qiwei [1 ]
Wang, Haiyan [1 ]
Shen, Lijun [2 ]
Chen, Xi [2 ]
Han, Hua [2 ]
机构
[1] Jiangsu Prov Inst Qual & Safety Engn, 3 Wenyuan Rd, Nanjing 210046, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
来源
MIPPR 2011: PARALLEL PROCESSING OF IMAGES AND OPTIMIZATION AND MEDICAL IMAGING PROCESSING | 2011年 / 8005卷
关键词
Empirical Mode Decomposition; Morphological Component Analysis; Image Super-resolution; Gaussian Mixture Model; MORPHOLOGICAL COMPONENT ANALYSIS; EMPIRICAL MODE DECOMPOSITION;
D O I
10.1117/12.911893
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper we propose an image super-resolution algorithm based on Gaussian Mixture Model (GMM) and a new adaptive image decomposition algorithm. The new image decomposition algorithm uses local extreme of image to extract the cartoon and oscillating part of image. In this paper, we first decompose an image into oscillating and piecewise smooth (cartoon) parts, then enlarge the cartoon part with interpolation. Because GMM accurately characterizes the oscillating part, we specify it as the prior distribution and then formulate the image super-resolution problem as a constrained optimization problem to acquire the enlarged texture part and finally we obtain a fine result.
引用
收藏
页数:8
相关论文
共 10 条
  • [1] Morphological component analysis: An adaptive thresholding strategy
    Bobin, Jerome
    Starck, Jean-Luc
    Fadili, Jalal M.
    Moudden, Yassir
    Donoho, David L.
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2007, 16 (11) : 2675 - 2681
  • [2] Morphological diversity and source separation
    Bobin, Jerome
    Moudden, Yassir
    Starck, Jean-Luc
    Elad, Michael
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2006, 13 (07) : 409 - 412
  • [3] Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA)
    Elad, M
    Starck, JL
    Querre, P
    Donoho, DL
    [J]. APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS, 2005, 19 (03) : 340 - 358
  • [4] The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
    Huang, NE
    Shen, Z
    Long, SR
    Wu, MLC
    Shih, HH
    Zheng, QN
    Yen, NC
    Tung, CC
    Liu, HH
    [J]. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971): : 903 - 995
  • [5] Colorization using optimization
    Levin, A
    Lischinski, D
    Weiss, Y
    [J]. ACM TRANSACTIONS ON GRAPHICS, 2004, 23 (03): : 689 - 694
  • [6] A study of Gaussian mixture models of color and texture features for image classification and segmentation
    Permuter, H
    Francos, J
    Jermyn, I
    [J]. PATTERN RECOGNITION, 2006, 39 (04) : 695 - 706
  • [7] Edge-preserving Multiscale Image Decomposition based on Local Extrema
    Subr, Kartic
    Soler, Cyril
    Durand, Fredo
    [J]. ACM TRANSACTIONS ON GRAPHICS, 2009, 28 (05): : 1 - 9
  • [8] Image quality assessment: From error visibility to structural similarity
    Wang, Z
    Bovik, AC
    Sheikh, HR
    Simoncelli, EP
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2004, 13 (04) : 600 - 612
  • [9] BANDWIDTH EMPIRICAL MODE DECOMPOSITION AND ITS APPLICATION
    Xie, Qiwei
    Xuan, Bo
    Peng, Silong
    Li, Jianping
    Xu, Weixuan
    Han, Hua
    [J]. INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2008, 6 (06) : 777 - 798
  • [10] Improved adaptive Gaussian mixture model for background subtraction
    Zivkovic, Z
    [J]. PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2, 2004, : 28 - 31