Illumination and Contrast Balancing for Remote Sensing Images

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  • معلومة اضافية
    • Publication Information:
      MDPI AG, 2014.
    • Publication Date:
      2014
    • Collection:
      LCC:Science
    • Abstract:
      Building a mathematical model of uneven illumination and contrast is difficult, even impossible. This paper presents a novel image balancing method for a satellite image. The method adjusts the mean and standard deviation of a neighborhood at each pixel and consists of three steps, namely, elimination of coarse light background, image balancing, and max-mean-min radiation correction. First, the light background is roughly eliminated in the frequency domain. Then, two balancing factors and linear transformation are used to adaptively adjust the local mean and standard deviation of each pixel. The balanced image is obtained by using a color preserving factor after max-mean-min radiation correction. Experimental results from visual and objective aspects based on images with varying unevenness of illumination and contrast indicate that the proposed method can eliminate uneven illumination and contrast more effectively than traditional image enhancement methods, and provide high quality images with better visual performance. In addition, the proposed method not only restores color information, but also retains image details.
    • File Description:
      electronic resource
    • ISSN:
      2072-4292
    • Relation:
      http://www.mdpi.com/2072-4292/6/2/1102; https://doaj.org/toc/2072-4292
    • Accession Number:
      10.3390/rs6021102
    • Rights:
      Journal Licence: CC BY
    • Accession Number:
      edsdoj.ff8863f7265647a4b55f6741253f736e
  • Citations
    • ABNT:
      JUN LIU et al. Illumination and Contrast Balancing for Remote Sensing Images. Remote Sensing, [s. l.], n. 2, p. 1102, 2014. DOI 10.3390/rs6021102. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.ff8863f7265647a4b55f6741253f736e&custid=s8280428. Acesso em: 14 dez. 2019.
    • AMA:
      Jun Liu, Xing Wang, Min Chen, et al. Illumination and Contrast Balancing for Remote Sensing Images. Remote Sensing. 2014;(2):1102. doi:10.3390/rs6021102.
    • APA:
      Jun Liu, Xing Wang, Min Chen, Shuguang Liu, Zhenfeng Shao, Xiran Zhou, & Ping Liu. (2014). Illumination and Contrast Balancing for Remote Sensing Images. Remote Sensing, (2), 1102. https://doi.org/10.3390/rs6021102
    • Chicago/Turabian: Author-Date:
      Jun Liu, Xing Wang, Min Chen, Shuguang Liu, Zhenfeng Shao, Xiran Zhou, and Ping Liu. 2014. “Illumination and Contrast Balancing for Remote Sensing Images.” Remote Sensing, no. 2: 1102. doi:10.3390/rs6021102.
    • Harvard:
      Jun Liu et al. (2014) ‘Illumination and Contrast Balancing for Remote Sensing Images’, Remote Sensing, (2), p. 1102. doi: 10.3390/rs6021102.
    • Harvard: Australian:
      Jun Liu, Xing Wang, Min Chen, Shuguang Liu, Zhenfeng Shao, Xiran Zhou & Ping Liu 2014, ‘Illumination and Contrast Balancing for Remote Sensing Images’, Remote Sensing, no. 2, p. 1102, viewed 14 December 2019, .
    • MLA:
      Jun Liu, et al. “Illumination and Contrast Balancing for Remote Sensing Images.” Remote Sensing, no. 2, 2014, p. 1102. EBSCOhost, doi:10.3390/rs6021102.
    • Chicago/Turabian: Humanities:
      Jun Liu, Xing Wang, Min Chen, Shuguang Liu, Zhenfeng Shao, Xiran Zhou, and Ping Liu. “Illumination and Contrast Balancing for Remote Sensing Images.” Remote Sensing, no. 2 (2014): 1102. doi:10.3390/rs6021102.
    • Vancouver/ICMJE:
      Jun Liu, Xing Wang, Min Chen, Shuguang Liu, Zhenfeng Shao, Xiran Zhou, et al. Illumination and Contrast Balancing for Remote Sensing Images. Remote Sensing [Internet]. 2014 [cited 2019 Dec 14];(2):1102. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.ff8863f7265647a4b55f6741253f736e&custid=s8280428