Analysis of the Wavelet Domain Filtering Approach for Video Super-Resolution

被引:0
|
作者
Daithankar, Mrunmayee, V [1 ]
Ruikar, Sachin D. [1 ]
机构
[1] Walchand Coll Engn, Dept Elect Engn, Sangli, Maharashtra, India
关键词
observation model; super-resolution; video quality parameters; wavelet residuals; wavelet domain processing; IMAGE; RECONSTRUCTION; INTERPOLATION; RECOGNITION; DISCRETE;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The wavelet domain-centered algorithms for the super-resolution research area give better visual quality and have been explored by different researchers. The visual quality is achieved with increased complexity and cost as most of the systems embed different pre- and post-processing techniques. The frequency and spatial domain-based methods are the usual approaches for super-resolution with some benefits and limitations. Considering the benefits of wavelet domain processing, this paper deals with a new algorithm that depends on wavelet residues. The methodology opts for wavelet domain filtering and residue extraction to get super-resolved frames for better visuals without embedding other techniques. The avoidance of noisy high-frequency components from low-quality videos and the consideration of edge information in the frames are the main targets of the super-resolution process. This inverse process is carried with a proper combination of information present in low-frequency bands and residual information in the high-frequency components. The efficient known algorithms always have to sacrifice simplicity to achieve accuracy, but in the proposed algorithm efficiency is achieved with simplicity. The robustness of the algorithm is tested by analyzing different wavelet functions and at different noise levels. The proposed algorithm performs well in comparison to other techniques from the same domain.
引用
收藏
页码:7477 / 7482
页数:6
相关论文
共 50 条
  • [41] Super-resolution enhancement of digital video
    Hardie, Russell C.
    Schultz, Richard R.
    Barner, Kenneth E.
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2007, 2007 (1)
  • [42] A 'deep' review of video super-resolution
    Gopalakrishnan, Subhadra
    Choudhury, Anustup
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2024, 129
  • [43] Super-resolution reconstruction of compressed video using transform-domain statistics
    Gunturk, BK
    Altunbasak, Y
    Mersereau, RM
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2004, 13 (01) : 33 - 43
  • [44] Plug-and-Play video super-resolution using edge-preserving filtering
    Ghassab, Vahid Khorasani
    Bouguila, Nizar
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2022, 216
  • [45] Global motion based video super-resolution reconstruction using discrete wavelet transform
    Wasnaa Witwit
    Yifan Zhao
    Karl Jenkins
    Sri Addepalli
    Multimedia Tools and Applications, 2018, 77 : 27641 - 27660
  • [46] Global motion based video super-resolution reconstruction using discrete wavelet transform
    Witwit, Wasnaa
    Zhao, Yifan
    Jenkins, Karl
    Addepalli, Sri
    MULTIMEDIA TOOLS AND APPLICATIONS, 2018, 77 (20) : 27641 - 27660
  • [47] HDR Video Super-Resolution for Future Video Coding
    Umeda, Seiya
    Yano, Niai
    Watanabe, Hiroshi
    Ikai, Tomohiro
    Chujoh, Takeshi
    Ito, Norio
    2018 INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY (IWAIT), 2018,
  • [48] Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach
    Liu, Ding
    Wang, Zhaowen
    Fan, Yuchen
    Liu, Xianming
    Wang, Zhangyang
    Chang, Shiyu
    Wang, Xinchao
    Huang, Thomas S.
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (07) : 3432 - 3445
  • [49] Super-resolution by pupil plane phase filtering
    Hazra, L. N.
    Reza, N.
    PRAMANA-JOURNAL OF PHYSICS, 2010, 75 (05): : 855 - 867
  • [50] Efficient Fourier-Wavelet Super-Resolution
    Robinson, M. Dirk
    Toth, Cynthia A.
    Lo, Joseph Y.
    Farsiu, Sina
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (10) : 2669 - 2681