A real time character image enhancement and interpolation algorithm for low-resolution image sensor

被引：0
|
作者：
Liang, FM [1 ]
Wu, SH [1 ]
机构：
[1] Taiyuan Univ Technol, Taiyuan 030024, Peoples R China
来源：
ICEMI 2005: Conference Proceedings of the Seventh International Conference on Electronic Measurement & Instruments, Vol 6 | 2005年
关键词：
real time; character image; wavelet; image enhancement; image interpolation;
D O I：
暂无
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：
As known, the image captured from low-resolution image sensor has worse vision effect. Especially, the character image has bluffed strokes, diffused lines as well as lower grey difference with background. In order to identify the character, we should effectively improve the character image resolution and definition by achieving real time character image processing. It is highly important for character image effect to choose proper image processing algorithm. At the same time, the processing progress maybe take too long time to be suitable for real time image processing. Based on analyzing features of character image, a rapid real time character image enhancement and interpolation method is introduced in this paper. The practical result has showed that the character image definition and revolution has been improved by almost double compared to the original image, and the character image stability has been greatly enhanced.
引用
收藏
页码：413 / 416
页数：4
相关论文
共 50 条
  • [1] Algorithm on extracting high-resolution image from low-resolution image sequence
    Shao, Ling
    Ding, Pei-Lu
    Zhang, Li-Ming
    Hu, Bo
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2001, 30 (01): : 58 - 61
  • [2] A gray-scale image based character recognition algorithm to low quality and low-resolution images
    Wang, XW
    Ding, XQ
    Liu, CS
    DOCUMENT RECOGNITION AND RETRIEVAL VIII, 2001, 4307 : 315 - 322
  • [3] An algorithm for resolution enhancement of low-resolution patterns captured by a sensor array
    Esmer, G. Bora
    OPTICS COMMUNICATIONS, 2014, 313 : 421 - 429
  • [4] Low complexity image enhancement GAN-based algorithm for improving low-resolution image crop disease recognition and diagnosis
    Salmi, Abderrahmane
    Benierbah, Said
    Ghazi, Mehdi
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (06) : 8519 - 8538
  • [5] Low complexity image enhancement GAN-based algorithm for improving low-resolution image crop disease recognition and diagnosis
    Abderrahmane Salmi
    Said Benierbah
    Mehdi Ghazi
    Multimedia Tools and Applications, 2022, 81 : 8519 - 8538
  • [6] Quality Enhancement of Low-Resolution Image by Using Natural Images
    Bilgazyev, E.
    Yeniaras, E.
    Uyanik, I.
    Unan, M.
    Leiss, E. L.
    SIXTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2013), 2013, 9067
  • [7] Low-Resolution Thermal Sensor-Guided Image Synthesis
    Chiu, Sheng-Yang
    Tseng, Yu-Chee
    Chen, Jen-Jee
    2023 IEEE/CVF WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WORKSHOPS (WACVW), 2023, : 60 - 69
  • [8] Deep Cooperative Enhancement Hashing Network for Low-Resolution Image Retrieval
    Dai, Feng
    Wang, Lei
    Zhu, Xiaobin
    Li, Haisheng
    Cai, Qiang
    IEEE ACCESS, 2020, 8 : 120114 - 120123
  • [9] Image Enhancement and Feature Extraction Based on Low-Resolution Satellite Data
    Syrris, Vasileios
    Ferri, Stefano
    Ehrlich, Daniele
    Pesaresi, Martino
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (05) : 1986 - 1995
  • [10] GRADIENT IMAGE SUPER-RESOLUTION FOR LOW-RESOLUTION IMAGE RECOGNITION
    Noor, Dewan Fahim
    Li, Yue
    Li, Zhu
    Bhattacharyya, Shuvra
    York, George
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 2332 - 2336
12345